Banking Study

THE BENEFITS OF INNOVATIVE INFORMATION TECHNOLOGY IN THE BANKING INDUSTRY IN TURBULENT TIMES. AN EMPIRICAL STUDY IN EUROPE AND NORTH AMERICA.

Banking Study

by Martin Hellmich, Mike Pinedo, Bjoern Schuck, Sikandar Siddiqui, and Axel Uhl

Figure 1: Contributions of process innovation and IT 6

Figure 2: Important features of management decision support information 7

Figure 3: Technology innovation in the future 7

Figure 4: Interview framework 9

Figure 5: Sector level clustering 10

Figure 6: Department level clustering 10

Figure 7: Business model 13

Figure 8: Complexity of asset/funding flows 13

Figure 9: Challenging environment 14

Figure 10: What is in-memory computing 22

Figure 11: Weighting Range 30

Figure 12: Importance of information technology 30

Figure 13: Process innovation 30

Figure 14: Importance of data 32

Figure 15: Capability of current systems and processes 32

Figure 16: Senior management decisions 32

Figure 17: Aggregation of data 33

Figure 18: New information technology 33

Figure 19: Gaps of service providers 33

Figure 20: Mobile banking 34

Figure 21: IT budget 34

LIST OF FIGURES

TABLE OF CONTENTS

1 EXECUTIVE SUMMARY 4

2 INTRODUCTION 8

3 FRAMEWORK OF THE BANKING STUDY 9

4 KEY DRIVERS OF CHANGE AND BEST PRACTICE PRINCIPLES 11 4.1 KeyDriverofChangesintheBankingIndustryIdentifiedintheStudy 11

4.2 Deriving Best Practice Principles Based on Experiences from the Crisis 12

5 MAIN TOPICS FOR DESK RESEARCH: KEY DRIVER OF CHANGES IN THE BANKING INDUSTRY 18

5.1 Changes in the Regulatory Framework 18

5.2 Developments in the Technology Environment 20

5.3 The Decisive Role of Mobile Technology for Banking in Africa 23

6 IN-DEPTH INTERVIEWS AND ELECTRONIC SURVEY: ANALYSIS AND KEY FINDINGS 25

6.1 Main Trends in the Financial Industry: Results from In-Depth Interviews 25

6.2 Changing Regulatory and Risk Management Requirements: Results from 27

In-Depth Interviews

6.3 Technology and Process Innovation: Results from In-Depth Interviews 28

6.4 Results of the Online Survey 29

6.5 Breakdown of Results for Key Markets 31

6.6 Results from a Regulators’ Perspective 35

7 BEST PRACTICE BANK 36

7.1 Creating Unique Value Together with Customers 36

7.2 Securing Compliance with Risk Management and Regulatory Requirements 38

8 CONCLUSION OF THE BANKING STUDY 46

9 AUTHORS 47

10 APPENDIX 48

11 LIST OF REFERENCES 66

4

Introduction | Banking Study

1 EXECUTIVE SUMMARY

Triggered by the financial crisis and the subsequent chang-es to their regulatory frameworks, banks are moving towards a new paradigm in managing risk, return, liquidity, and capital simultaneously and proactively. In doing so, they face several challenges: stricter regulation and an increasing intensity of su-pervisory control have led to substantially higher demands on their risk management infrastructure. In conjunction with higher macroeconomic volatility and a slowdown in growth in Europe, Japan, and the US, and intense competition, this has led to a protracted erosion of profit margins in many of the established business lines and locations. On the other hand, “megatrends” such as variations in customer demands and behavior, shifts in geographical, political and economic power balances, as well as demographic changes and innovations in information technol-ogies, offer new opportunities for future business. Hence, stra-tegic innovation is essential for a successful revision of current business models and to differentiate future business models from competition. As a senior executive from a leading US-Bank put it “Innovation is also not limited to leveraging next gener-ation technology capabilities. Innovation can also come in the form of strategic improvements around both talent and process management.” Innovation efforts are equally related to new products, services as well as business practices, and are mirrored by higher requirements to the technical frameworks of banks and their use of innovative IT solutions.Against this background, SAP AG and the Business Transformation Academy in Basel, Switzerland, have partnered with the Frankfurt School of Finance & Management and the New York University’s Stern School of Business and Management to conduct a joint re-search project, which seeks to identify a number of methods and procedures in value chains and risk management approaches of banks with business models of different size and complexity of which the outcomes have been consistently superior to others, and which can, consequently, be labeled as “best practices” in this field. The goal is to explore how identified best practice approach-es can be reflected in a state-of-the-art framework by leveraging the benefits of advanced and innovative information technology.

Research Goals: • Analyze the current and future mega trends and challenges

in the banking sector• Identify the major drivers for business transformation in

the financial industry• Understand the impact of innovative technology on future

business models• Describe the characteristics of a best practice bank• Explore the roles of customers and supervisory authorities

in reshaping the banking value chain

Setup of the StudyThe study consists of a thorough analysis of current drivers and innovation trends in banking, and describes how they relate to the current business challenges. A specific goal of the study is to investigate how innovative technology can shape interactions with stakeholders, enhance risk management and compliance, and create integrated global value chains. The study builds on three pillars:

1. Extensive desk research2. A series of 20 in-depth interviews with C-level bank man-

agement executives, and executives at regulatory authori-ties as well as audit firms

3. A web-based survey resulting in responses from 230 medi-um level executives from different financial institutions.

The interviewees include representatives of supervisory au-thorities, e.g. the U.S. Securities and Exchange Commission and Deutsche Bundesbank, leading audit firms like KPMG and PwC, and leading banks, e.g. JP Morgan, Barclays Bank, and Deutsche Bank. Due to the composition of the respondent group, the geo-graphical focus of the investigation is mainly on Europe and North America, although some insightful contributions came from Africa, as well.

Study ResultsThe analysis reveals a clear consensus that the “originate-to-dis-tribute” business model which dominated before the crisis is now outdated. Regulators demand that banks implement a long-term sustainable business model instead of focusing on short-term profit maximization. On the other hand, there is large pressure to accelerate the process of change and business model transformation. As a senior representative from a large German bank put it “the felt perception of a two year project is to have an infinite duration. There is pressure for short term success and execution. Key for new technologies is to achieve long term improvements in a short time horizon.” Among the main challenges are low profit margins, the volatile macroeco-nomic outlook, intensified competition and rising IT costs due to new regulations.

The Key Drivers for Business Model Transformation:1. Changing regulatory and risk management requirements2. Technology and process innovation3. Variations in customer behavior and preferences

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The recent amendment of the Basel Accord on Banking Super-vision will require banks to strengthen their equity base and control their liquidity situation more stringently. As a senior ex-ecutive from a German bank put it “the stricter and increasingly extensive regulatory requirements now constitute the greatest challenge for banks.” In the context of Basel III, the supervisory authorities have raised their data requirements in terms of quan-tity, detail, accuracy, and speed of delivery. According to a senior executive from a regulatory authority, the main challenges are “automated ad hoc stress testing functionalities, correct, com-plete, granular product data, timely balance sheet data, timely and complete counterparty data for the entire bank or group. This requires bank-internal systems to be improved continuously and hence places high demands on the technology in use.” A se-nior executive from a regulatory authority made the clear state-ment that “we estimated that a great percentage of the currently implemented processes with most of the banks are insufficient to meet future requirements.” His colleague from another super-visory authority confirmed this view: “IT budgets have to signifi-cantly increase to meet the current and future requirements.” Moreover, the Dodd/Frank Act and European Market Infrastruc-ture Regulation (EMIR) will have a profound impact on the reg-ulatory landscape. One U.S. interviewee predicted that “as a result, more trades will be driven to clearing houses and other trading platforms. Margins may well compress in this process but at the same time new business opportunities will emerge, for example, in the area of client collateral management.” It is ob-vious that due to the strict margining and collateral rules which such a move implies, data management within banks will have to become more efficient, which can only be fulfilled by an inte-grated and scalable IT infrastructure. However, risk management is by no means limited to the ful-fillment of regulatory standards alone. Instead, it is increasingly understood as a key driver of competitive advantage. As Dr. Marc D. Grüter of Roland Berger Strategy Consultants put it “there is a direct relationship between the quality – i.e. the effective-ness of risk management, and the sustainability of profit devel-opment.” 1 According to this understanding, a bank’s Chief Risk Officer needs to act as a mediator between the CEO and those top-level executives responsible for market-oriented activities.

Technology and Process A main challenge is the improvement of important information flows like current liquidity and risk profile which is often sum-marized by the key term Real Time or as a senior executive from a global bank phrased it: “MDs must be able to get the informa-tion they need at any time; what, where, how, and why. There must be one responsible person in the company who also needs to manage that on the level of the system.” This is supported by the statement of a German senior executive: “New corporate governance regulation states that DAX corporate board mem-bers need to be aware about all risks within their company also if it is not their resort. That can obviously only be done with a perfect IT infrastructure and predefined and explained figures or information, available at any time. The information needs to be delivered in such a way that each board member understands and values it.”

But technology is not just a means for a tailored reporting pro-cess to effectively inform the management or for adapting to new regulatory requirements. Rather, according to a leading U.S. bank executive “one of the key imperatives for IT is the align-ment of technology initiatives with business priorities. The key focus areas for IT are typically improving customer experience, enabling growth, improving productivity/efficiency, and reduc-ing risk.” Another interviewee concisely concluded that “there is a lot of IT without banking, but there is no banking without IT.” Here, the key terms are big data, mobile technology and cloud computing. With regard to the former, a senior executive from a large US-Bank asserted: “By harnessing big data we will reduce costs and make our operations more transparent to ourselves and our regulators. We will develop new approaches to mitigate risk, including faster and more effective identification of fraud and other illegal and costly activities. Using big data and ana-lytics, we will provide new opportunities and services for our customers by developing tools and providing enhanced infor-mation that will allow them to make better decisions regarding their businesses. We are at the beginning of a new age of mas-sive and real-time information and analytics and if we proceed wisely, it will have a positive impact on everything that we do.” With regard to the latter, concerns regarding the potential in-security and lack of privacy protection were primarily voiced by supervisory bodies and only to a lesser extent by banks. A senior executive from Deutsche Bundesbank made the statement that “in the case of Germany, the Bundesbank sees the Cloud not as secure enough to be used in banks. Germany is complicated and conservative in this type of changes.”

Variations in Customer Behavior and Preferences The key to re-building trust and improving relationships with customers lies in enhanced cooperation and communication to adjust the product and service portfolio to the needs of the cus-tomers. As a representative from a British bank stated “one of the most delicate challenges is the trust that clients have in the institutions. For customers, business transparency is an ongoing concern and money is a very sensible subject.” When dealing with information technology, challenges and opportunities are implied: A representative of a bank with a large retail segment confirmed that “the digitalization of retailbanking, e.g. through mobile payment calls for a process sim-plification. It is accompanied by a strong increase in the num-ber of customer channels. Through Web 2.0 and Social Media applications, banking has become increasingly interactive. These applications are strongly used by businesses and private citizens to decide which companies they deem reliable, what products they should buy, and - a very important fact - to let others know how they were attended to.” In response, many banks have been investing heavily in applications for tablet com-puters and mobile phones with internet connectivity that enable customers to conduct a large variety of transactions en route. At least some of them also use the capabilities of social networks to attract “fans” to full-featured social network pages, seeking to strengthen the image of their brands and to have consumers share personal information. A senior executive from a large US-Bank summarized his projections for his client base as follows:

1 Source: Roland Berger Strategy Consultants, Press Release, Zurich, February 18, 2014.

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• “Over 25% of mobile phone users access financial services content on their phone. Financial services growth on mobile apps has increased to 53% YoY

• Paying credit card bills via mobile grew 30% over the past quarter• Remote check deposit increased to 40% in past quarter • 24% of current banking customers with smartphones trans-

fer money via mobile• Banks will need to continue to evolve with changing con-

sumer behaviors as the predicted inflection point of mobile vs. PC banking is expected by the end of 2015.”

A colleague from a leading German bank agreed with him: “Mo-bile Banking will be a main distribution channel for standard retail products with low counselling intensity.” Against this background, Vincent Piron, a partner at KPMG Bel-gium, reckons that “over the long term, social media will become enmeshed into the organizational fabric [of financial institu-tions] in much the same way that the telephone, the internet, and email did before them.” 2 However, use of technology alone will not automatically be a source of competitive advantage. Creating added value requires a lot more than pinning technologically sophisticated applica-tions onto a traditional business model. More specifically, the study reveals the three strategic needs to 1) synchronize tradi-tional and new banking channels, 2) re-design bank branches and 3) use technology to facilitate organizational learning.A colleague from a leading German bank agreed with him: “Mo-bile Banking will be a main distribution channel for standard retail products with low counselling intensity.” Against this background, Vincent Piron, a partner at KPMG Bel-gium, reckons that “over the long term, social media will become enmeshed into the organizational fabric [of financial institu-tions] in much the same way that the telephone, the internet, and email did before them.” However, use of technology alone will not automatically be a source of competitive advantage. Creating added value requires a lot more than pinning technologically sophisticated applica-tions onto a traditional business model. More specifically, the study reveals the three strategic needs to 1) synchronize tradi-tional and new banking channels, 2) re-design bank branches and 3) use technology to facilitate organizational learning.

Breakdown of Result for Key MarketsRegarding mega trends and future challenges driven by regula-tory and risk management requirements, the markets in Europe and the U.S. are very similar. Moreover, the assessment of pre-vailing strategic challenges and the necessary management re-sponses are comparable for these two regions. American banks have on average made better progress in recovering from the re-cent financial crisis than their European counterparts. As a con-sequence, the leading American banks have far more resources available to prepare for the necessary transformation of their business models and for strengthening their foothold in grow-ing market segments, e.g. in the newly advanced economies of Latin America, Eastern and Southern Asia, and Africa.In many the markets for which higher growth rates are expected

for the near future, distribution channels for financial services differ a lot from those in established market economies. In both Latin America and Sub-Saharan Africa, the availability of ba-sic banking services via mobile phones is a prerequisite for a majority of the population to access the financial markets. In many of these regions, however, the start-up costs associated with the establishment of new banking offerings are consider-able because of substantial investments in technological infra-structure needed for the build-up of new distribution channels. Those large U.S. banks which have advanced further in restor-ing their financial health than their European counterparts can be reasonably expected to have a significant advantage in the global competition for market shares.

Key Lessons Learned• Banking is all about confidence. Hence, the banks that will

emerge best from the recent shake-up within the sector will be those that have access to reliable information about customer needs and concerns, and use it to make the most attractive offer through the most appropriate channel to the right individual at the most suitable time.

• Carefully identifying, measuring, reporting, and steering risk is not just a regulatory duty but an integral part of the value creation process. The more this principle is put into prac-tice, the better the new regulatory framework can be turned from a burden into an opportunity.

• Competent use of recent advances in information technol-ogy, like real-time analytics, in-memory computing, and (to some extent) Cloud Computing can contribute significant-ly to resolving the trilemma posed by new regulatory de-mands, eroding profit margins, and increasing client service demands.

Survey Results HighlightsThe contributions that process innovation and IT can make are considered highest in the fields of regulatory compliance and customer satisfaction (77%). The cost reduction and revenue enhancement effects of these factors are, on average, deemed less pronoun:

Process innovation and IT can help with...

0% 20% 40% 60% 80%

Reducing costsIncreasing revenues

Improving customer satisfactionMeeting regulatory requirements

0% 20% 40% 60% 80% 100%

2 Source: KPMG International (2013) Figure 1: Contributions of process innovation and IT

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When it comes to supporting management decisions, respon-dents place greatest emphasis on the aggregation and compre-hensiveness of information. The availability of real-time infor-mation receives considerably less weight:

Important features of management decision support information include

0% 20% 40% 60% 80% 100%

Figure 2: Important features of management decision support information

Simulation and stress testing

Aggregation and comprehensiveness

On-demand drill-down functionality

Real-time analytics

Among current technology innovations, mobile computing at-tains the highest average importance score, with Cloud and in-memory computing lagging far behind:

A technological innovation of high relevance in th

e future is...

0% 10% 20% 30% 40% 50% 60% 70%

Figure 3: Technology innovation in the future

Mobile computingCloud computing

In-memory technology

A finding of high importance for technology providers is that while 60% of respondents expect their institution’s budget for information technology to increase over the next three years, only a small minority anticipates a budget increase of above 25% in this time span.

Conclusions: Characteristics of a Best Practice BankIn spite of the considerable heterogeneity of the banking land-scape in the main target regions of this study, the survey, the in-terviews, and desk research on which it is based led to the con-

clusion that there are five common traits which banks that are practice leaders in their field have in common, and could thus be described as common characteristics of a “best practice bank”.

• People within a best practice bank are keen listeners and attentive observers when it comes to identifying custom-er’s needs and wishes, and strongly focused on gaining and keeping customers’ trust through product and service offer-ings of lasting value. A best practice bank encourages and swiftly responds to customer feedback, seeking to turn crit-icism into opportunities for learning and improvement, and uses technology as a means to this end.

• Decision makers in a best practice bank are aware of the fact that risk management is not primarily a modeling ex-ercise under the exclusive responsibility of a group of pro-fessional fearmongers but a vital part of just about every-body’s business. A risk management executive interviewed in the research phase of the project summarized this point very precisely: “The firm’s risk management framework is intended to create a culture of risk awareness and personal responsibility throughout the firm where collaboration, dis-cussion, escalation, and sharing of information are encour-aged. Technology is a key enabler to effectively deliver on the objectives of risk management.”

• A best practice bank takes the recent regulatory amend-ments as an inducement to overcome existing bottlenecks within the present IT infrastructure not by trying to enhance legacy systems in a piecemeal manner but by moving to a new, integrated framework which secures data consisten-cy and integrity. Supervisory authorities will appreciate the greater speed, reliability, and accessibility of risk-related in-formation and the qualitative enhancement of risk manage-ment processes this brings about.

• Executives in a best practice bank are aware of the fact that the information on customer demands and behavior, mac-roeconomic environment factors, money and capital market developments, and internal performance and risk indicators, which it gathers in the course of its daily business, becomes one of the organization’s most valuable assets if competent-ly used. A best practice bank therefore actively draws on the capability of in-memory data processing to accelerate and facilitate access to information coming from heterogeneous sources and in various formats, thus improving the reliabil-ity, speed, and appropriateness of decisions. It also uses the potential of Cloud Computing when seeking to achieve data coherence and economies of scale in data manage-ment. Moreover, the bank closely interacts with technology providers in order to align IT concepts with bank-internal organization structures and workflows, and to maintain a common understanding of the demands on, and the oppor-tunities offered by, technology.

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2 INTRODUCTION

The extensive usage of leverage on bank balance sheets, es-pecially in the United States and Europe, together with regu-latory arbitrage led to one of the worst worldwide crises with defaulting banks and large state rescue packages and even bail outs of sovereign European countries. The claims and lobbying by large international banks for de-regulation opened the way for large balance sheets with little equity, creative offshore solutions and misuse of the securitization technic. After exten-sive years of development of the financial system, one small wheel, in this case the US housing market, fell and revealed the puffed up system. The domino effect turned out to be stronger than expected and finally opened the process for a complete rethinking of the regulatory financial framework. This process obviously has already started and resulted in several new or stronger regulations. For example, Basel III increased the equity needs and installed a liquidity ratio (CRD IV package – including also CRR – Capital Requirements Regulation), new proposals for derivatives like EMIR were developed over the past 12 month; the Bank Recovery and Resolution (BRR) Directive started in 2013 and the Liikanen Plan was delivered by a High-level Expert Group by October 2012. The overall target is to restructure the banking system in such a way that it can stand on its own legs even in a strong crisis. From a more general perspective, banking is the business of managing information flows as a core financial intermediary in a dense network of different market participants especially bor-rowers and investors. In today’s globalized world, financial net-

works are larger and more complex and given modern technol-ogy, the information flows have become exponentially greater and faster. Banking is now virtual and the intrinsic value of a bank is the existing network of relationships, and fast access to all relevant information regarding existing and in the near future, ongoing funding, asset and information flows in this network, as well as the ability to manage the business opportunities and the risk inherent in these flows. Therefore, a bank is part of the core activities to be a leading operator of advanced information technology and this statement is even more meaningful as the institution’s business model becomes larger and more complex and more counterparties in the financial network are covered.In the future, a sustainable business model and attention to risk management and regulation is needed. Against this back-ground, SAP AG and the Basel-based Business Transformation Academy have partnered with the Frankfurt School of Finance & Management and the NYU Stern School of Business to conduct a joint research project This project seeks to identify a number of methods and procedures in value chains and risk manage-ment approaches of banks with business models of different size and complexity of which the outcomes have been consistently superior to others, and which can, consequently, be labeled as “best practices” in this field. The goal is to explore how iden-tified best practice approaches can be reflected in a state of the art framework by leveraging the benefits of advanced and innovative information technology.

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Framework of the Banking Study | Banking Study

The action plan for the Banking Study comprised three pillars. It began with extensive desk research, followed by 20 in-depth, high-level interviews of banks, regulators, auditors and consul-tancies from the USA and Europe, and finished with an online survey of the alumni network of Frankfurt School of Finance & Management with 230 usable results.The interviews were jointly conducted by the Frankfurt School of Finance & Management for the European area and the NYU Stern School of Business as a partner for the United States. It was important to choose the institutes as broadly as possible on a geographical as well as sector and topic perspective. The interviewees were restricted to the top to upper management of the respective institute or the specialized division, like risk management, front office or IT (see figure 4).

The desk research phase paved the way for the ongoing study. The official documents constituting the new regulatory frame-work for the international banking system were examined and their likely implications determined, drawing on the relevant related publications and expert opinions from audit firms and business academics. Some of the top trends in the field of in-formation technology were sought, identified and examined by their relevance for the banking sector, combining some literature research with experiences gathered by the team while working

as practitioners and advisors. In doing so, both the relationship of the bank with its current and potential customers and the way bank-internal processes and information flows are shaped by both regulatory requirements and the quest for sustainable value creation were taken into account.The first step was to identify, mostly based on desk research, the main topics for the questions to be asked. Four main subject areas, Mega Trends, Risk and Compliance, Capabilities of Pro-viders and Mobile Banking, were identified and explored using different numbers of individual questions. “Mega Trends” was intended to provide an overall impression of the importance and challenges of IT and risk management in the near future and how new topics like cloud computing, in-memory technology and big data are viewed. The section Risk and Compliance was the main section within the questionnaires and tried to focus in detail on specific tasks like the possibility to deliver real-time data or reporting in general, current setups and needed changes to fulfill current regulatory frameworks. Capabilities of Providers were implemented to show strength and weaknesses in the eyes of the market regarding the behavior, setup and general activities of IT solutions providers. Finally, the section Mobile Banking was explicitly created as desk research showed a huge potential for all areas of internet or mobile based activity.The second step was to identify a list of potential participants over different sectors and regions. It was possible to conduct interviews with well-known institutes such as JPMChase, Mor-gan Stanley, Barclays, Commerzbank, Deutsche Bank, Deutsche Pfandbriefbank, Hessische Landesbank, DZ Bank, FMS, HSH Nordbank, ING, the U.S. Securities and Exchange Commission, Deutsche Bundesbank, PriceWaterhouseCoopers, KPMG and Booz & Company. As a side project interviews were performed with the Banque of Mocambique (central bank) and the Standard Bank Africa, to gather some information from developing countries where, for example, mobile banking is more common compared to in Europe and the United States. Finally, the interviews were either carried out as a real face-to-face interview, or delivered and filled out by senior management of the appropriate division. The overall distribution of seniority levels of participants can be stated as 12.5% coming from the

3 FRAMEWORK OF THE BANKING STUDY

“Frankfurt School of Finance & Management is a research-led business school, covering every aspect of business, management, banking and finance. An impressive portfolio of services – ranging from degree courses to Executive 1111Education programs, from research projects to consultancy – means that Frankfurt School acts as adviser, catalyst and educational partner to companies and organizations, to individuals embarking on new careers, and to experienced executives. As a center of intellectual and practical activity, the business school formulates forward-thinking solutions for the worlds of business, finance and management, where agendas and issues are constantly changing.” (FS 2013)

“Since its inception in 1900, New York University Stern School of Business has been in and of New York City. Founded as the School of Commerce, Finance and Accounting, the School initially offered training to students for careers in commerce in the burgeoning financial markets of New York City. Today, located in the heart of Greenwich Village with a campus in Westchester, Stern is one of the nation’s premier management education schools and research centers with a broad portfolio of academic programs at the graduate and undergraduate levels. With its global partnerships and engagement in NYU’s global network university, today NYU Stern is not only in and of the city, but also in and of the world.” (NYU 2013)

Commercial bank

Retail bank

Investment bank 2nd levelC-level

Front office

3nd level

IT

Universial bank

US

Europe

Type of Institution

Topic

Area

Seniority

Risk management

Figure 4: Interview framework

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Framework of the Banking Study| Banking Study

first layer of management, 25% from the second layer (senior vice president or equivalent), and 62,5% from the third layer or below (vice president/director) .

Online SurveyIn addition to the questionnaires presented to senior manage-ment of banks or regulatory entities, an electronic field studyvia an online survey accessable under www.scdm.de was con-ducted. The goal was to get broader result of the needs and opinions throughout the financial markets, across all levles of seniority. The targeted group was the alumni association of the

Frankfurt School of Finance & Management which consists of more than 1,500 national and international former students. The study was closed on the October 15, 2013 with usable feed-back from 230 participants. Participants were asked to answer 10 multiple choice questions and to submit their company and department names for clustering purposes. All questions were to be answered using a scale ranging from 1 (“not important/not at all”) to 5 (“very important/to a large extent”). During the evaluation of the survey, votes for categories 1 and 2 on one hand, and categories 4 and 5 on the other, were combined to form the meta-categories “not important/negative” and “im-portant/positive” respectively. In order to enable a comparison of the different questions and subquestions, a weighted average voting factor was calculated, multiplying the vote 1-5 with the number of votes setting the NA as 0. A high number indicates a strong and clear result (See table in appendix).

Analysis of the ParticipantsThe survey was built to give detailed information about the department or just general infomation about the company for which the participant works. Thus, it was possible to cluster in two ways; firstly based on the typical working field of the company and secondly based on the actual activity across all types of companies. The company level was split into Asset Man-agement, Auditing, Banking, Consulting, Corporates, Financial Services, No Information and Others, no matter which specific department the participant is working in. This can lead to some unclear situations, as consultants exist in consulting companies, but also within typical auditors such as KPMG or PwC. For the first analysis, a consultant working for KPMG was listed under Auditor as the company level and for the second analysis under Consulting. Considering Frankfurt School of Finance & Man-agement, as a private university with a focus onfinancial mar-kets, it does not seem surprising that the 7% share of Corporate employees is quite small. Most of the participants are out of the Banking industry (53%), which includes every bank with a banking license. Together with the Financial Services entities, which are brokers or financial firms without a banking license, the overall targeted group Banks comprises up to 57% of the survey,a long way ahead of Auditing (9%), Corporates (7%) and Consulting (5%). However, 16% or 37 persons did not deliver information to cluster them correctly (Figure 5).Looking at the department or working area of each participant, no matter what kind of company, it is interesting to see that the strongest group are the Consultants, followed by Investment

Banking, Audit, Corporate Banking and Private Banking, Wealth or Retail Banking (Figure 6). Obviously, Investment, Corporate, Private, Wealth and Retail Banking are not real departments, but it wasn´t helpful for this study to cluster further into their

subcomponents. Some departments like Treasury, Sales or IT are important on the regulatory side as well, as they do exist outside of banks, which is why they are mentioned seperately. One further impovement of this clustering should be to distin-guish between sector and department fields and to state both. Nevertheless, it is important for the interpretation of the study that it reached the right people.

Consultant

Investment Banking

Retail Banking / Private Banking / Wealth Management

Audit

Corporate Banking

Sales

IT

Treasury

Asset Management

Controlling

12%

13%

16%4%

5%

6%

10%

10%

12%

12%

Figure 6: Department level clustering

Asset Management

Auditing

Banking

Consulting

Corporate

Financial Services

No Information

Others53%

9%

4%2%16%

4%

7%

5%

Figure 5: Sector level clustering

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Key Drivers of Change and Best Practice Principles | Banking Study

4 KEY DRIVERS OF CHANGE AND BEST PRACTICE PRINCIPLES

In the first phase of the research study we conducted a detailed desk research analysis. The authors of the study are all experts with many years of professional banking experience. We have combined this track record with a wide range of publicly avail-able information from many sources to identify a broad set of key drives of change and for the future common accepted best practice principles for the banking industry. In a later stage of the study we adjusted our findings by conducting an empirical study, comprising in depth expert interviews and an electronic survey. We will describe the identified key drivers and best prac-tice principles below and in the following parts of the report we will show how this list of drivers and principles is justified by the results from desk research, in-depth expert interviews, and electronic survey.

4.1 Key Driver of Changes in the Banking Industry Identifiedin the StudyThe analysis revealed a clear consensus that the pre-crisis ver-sion of the “originate-to-distribute” business model which dom-inated before the crisis is now outdated. Banks are now in the mode of focusing on so called core business fields by reducing of their activities in former attractive segments, such as securiti-zation, correlation products, complex derivative and proprietary trading, structured solutions for regulatory and tax arbitrage, amongst others. For example, today in Germany we find high competition in traditional business fields, like SME-Financing, which were considered in pre-crisis times an activity with poor risk/return profile. In light of the absence of previous opportuni-ties, many banks in Germany have discovered the “Mittelstand” (i.e. small or medium sized enterprises) as a new core compe-tence and even accept a considerably negative P&L impact to increase their market share and to drive competitors out of the market. This leads to all time low refinancing costs for SMEs in Germany but RoE-Expectations for German banks will stagnate at a poor level. From today’s point of view, there is no convincing strategy of how to fulfill regulators’ demand for banks to adopt long-term sustainable business models rather than focusing on short-term profit maximization. The main challenges include low profit margins, the volatile macroeconomic outlook, inten-sified competition, and rising IT costs due to new regulations. We expect, especially for the European banking industry, strong consolidation tendencies in the long run, with surviving entities finding compelling answers to the key drivers for change. We have identified the following three key drivers for fundamental business model transformation:• Changing regulatory and risk management requirements:

Regulatory amendments crystallized as the main drivers of business model changes and require an integrated and efficient IT infrastructure as well as data management.

This will necessarily increase costs while products’ margins shrink. In particular, representatives from regulatory au-thorities and auditors clearly articulated the view that the increasing degree of harmonization among different sets of regulatory requirements like IFRS, Financial Reporting Standards, Basel III and BCBS 239 creates an urgent need for banks to replace existing data and reporting silos with information systems capable of operating reciprocally with others, enabled by new data warehousing technologies. Risk management, rather than focusing only on the ful-fillment of regulatory standards, increasingly assumes the role of a key business partner and acts as a mediator be-tween the CEO and those responsible for market-oriented activities, particularly trading. In this capacity, risk manage-ment and the efficiency of the Internal Capital Adequacy Assessment Process (ICAAP) is regarded as a key driver of competitive advantage in the banking industry. Besides the role of ICAAP as a target of the supervisory review process (second pillar of the Basel framework) and of market dis-cipline (third pillar of the Basel framework), we consider the performance of the ICAAP process as a key for future business opportunities. We believe that this statement is valid for all main business models in the banking industry and covers both pure banking book institutions and trading book institutions. For example, historically the loan busi-ness in the SME segment has shown poor profitability. As a consequence of redesigning business models, many insti-tutions focus on local business and SME in particular, and stronger competition in combination with increasing cap-ital and liquidity requirements driven by Basel III will put further pressure on margins. In this environment, optimiz-ing credit processes can deliver key competitive advantag-es. Introducing simplified and automated processes across the value chain of credit related ICAAP components like Internal Rating Based Models, Early Warning Systems, Limit Management and Capital Allocation Processes and better alignment of credit processes to the specific business seg-ments enable the banks to carry out more efficient deci-sion making. This will result in an optimized cost base and enable financial institutions to capture more business due to faster credit decisions and more competitive business offerings. The effects of market discipline cause external components, like funding costs and other important factors for the lending business, to be influenced by the quality of the credit process. In the capital market business, like mar-ket making, trading desk activities, repo, securities lending or collateral transformation services, banks are faced with additional challenges, which are posed by the availability of real-time credit and market data for calculation of the

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Basel III Credit Value Adjustment Charge, or by technolog-ical processes for enterprise wide collateral management needed to optimize the use of available collateral. Success-fully dealing with these challenges means creating vital competitive advantage for costs of capital and liquidity and again leads to increasing market share. Re-engineering the different ICAAP-relevant risk management processes is a key requirement. This statement leads us to the second driver of change as it is intertwined with a broad range of technological requirements, including the existence of cen-tral data warehouses, highly automated process chains, and availability of real-time analytics.

• Technology: As we have already established that technolo-gy is the main ingredient for creating competitive advantage by increasing the efficiency of the ICAAP processes, we can now apply this concept to the entire banking organization. Thanks to technological innovations, data management, workflow, and client/customer interactions are chang-ing dramatically. The interviewees, especially those from banks whose business is positioned globally, emphasized their assessment that the arrival of big data and real-time information and analytics constitutes a new era in informa-tion technology. New technologies are the key to targeting new markets and client groups with new kinds of financial services sold through innovative distribution channels. At the same time the rise of the network economy creates new competitors: Banks are faced with higher substitution of products and providers. The next two decades will be driven by demographic changes, geopolitical power shifts, the growing strength of the emerging markets, and cross border integration of value chains. Especially for banks headquartered in developed countries but aspiring a global business model, it will be a clear opportunity to participate in these developments and to create a new growth story in order to diversify the consequences of the expected consol-idation process in the mature economies, i.e. those charac-terized by stable or declining populations and experiencing a slowdown in growth. We expect fundamental changes in banking based on innovations in information technology and the accelerated creation of knowledge.

• Customer centricity: Enhanced cooperation and communi-cation can be seen as the key to rebuilding trust and im-proving relationships with customers especially in the ma-ture economies. There is a lot of room for banks to evolve in the way they characterize their clients’ goals and risk tolerance. Traditional bank services fail to capture the complexity of people’s lives nowadays. Characterizing the real risks that affect people’s lives (medical, housing, de-pendent parents, etc.) and then building options to allow people to self-insure where they wish, and farm out seg-ments of that risk with stop-loss can be part of adapting financial and investment management services to changing client demographics and environments. Driven by expan-sion strategies to emerging markets the retail demograph-ics for global banks will become younger. Consequentially,

market leaders will be forced to move away from the tra-ditional tools like paper-based statements and reporting, to service delivery in line with other services these client groups are accustomed to. This means banks will be forced to deliver better online services, clearer and more creative presentation of quantitative data and to offer online chat rather than telephone interactions. Using big data and an-alytics will also provide new opportunities and services for customers by developing tools and providing enhanced in-formation that will enable them to improve their business decisions. Adjusting products and services to the needs of customers with the help of new opportunities created by innovations in IT such as mobile phones, interactive digital devices, and social networks can be the guide for future growth paths.

4.2 Deriving Best Practice Principles Based on Experiences from the CrisisThe classical banking business mainly consists of taking short-term deposits and granting mid- to long-term loans. This is still the business setup especially for regional banks as private or savings banks and credit unions. International investment banks changed this business model from “originate to hold” to the “originate to distribute” approach (see figure 7) and thus changed the whole risk approach with long term influence on the worldwide real economy. Suddenly, loans were granted to persons or companies of low credit quality merely to directly sell these loans to the capital market. The main counterexample today for best practice in terms of management of information, funding and asset flows is the se-curitization technique of the pre-crisis style, which has created very complex financial intermediation chains. Securitization is the process of transforming reference portfolios of loans (or other assets) into specific forms of debt security, which can be sold to investors. Differing from traditional business models, where Banks accept deposits and utilize their comparative ad-vantages to transform deposits into loans (“Originate to Hold”) Banks became brokers in credit risk between ultimate borrow-ers and those who either purchased Asset Backed Securities (ABS) or who offered CDS insurance (“Originate to Hold”). At the same time as banks assumed the role of being investors in highly rated ABSs, the asset-side of the banks’ balance sheets usually incorporated high-rated (AAA) securities which required no significant capital reserves and low Risk Weighted Assets, but which still carried a higher premium in comparison to the banks’ own liquidity charges. Typically, this process involves a very complex intermediation chain: It starts with poor credit processes and adverse selection of assets by the originating bank, and involves shifting out the complete credit risk of the asset pool so that there is no alignment of interest with the next investor in the chain. Shin (2009) formulated the “Hot Potato Hypothesis”: Securitization allows for a “hot potato” of bad debts to pass down a chain of principal-agent problems. This continues as long there is a greater fool next in the chain and ends with the final investor who is the greatest fool. The conclusion is that “the banking system is the greatest fool” as the main final risk takers in the chain are again banks. The complexity of these

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chains is shown in the figure 8.Instead of processing information delivered by the original bor-rower and executing a qualified credit process based on this data, investors relied on externally assigned credit ratings. Higher ratings were justified by various credit enhancements including overcollateralization (i.e. pledging collateral in excess of debt issued), credit default insurance and equity investors willing to bear the first losses. Banks, in their role as main end investors into securitized assets, finally transformed the original long term credit risk into short term refinancing and liquidity risk. The pre-crisis business model of banks was characterized by exces-sive leverage and high maturity mismatch (on/off balance sheet) in the banks and the related shadow banking system (SPVs, SIVs, and Conduits). The maximization of lending capacities, sup-

ported by regulatory capital arbitrage, rating arbitrage, and an extraordinary expansion of credit risk transfer instruments, re-sulted in huge financial imbalances in the form of overstretched balance sheets or excessive off-balance sheet risk exposure. This first led to rising asset prices and strong economic growth and second to credit related bubbles (housing, LBO&MBO, commer-cial real estate). Finally, the acceleration of financial innovation enabled banks to transfer hedging and active trading of credit risk as a separate asset class and led to fundamental structural changes in the financial system.Wall Street underwrote $3.2 trillion of loans to homebuyers with bad credit and undocumented incomes from 2002-2007, and structured Mortgage Backed Securities (MBS) and Collat-eralized Debt Obligations (CDOs) that received high ratings and

Deposits Bank

BorrowerBalance Sheet:Loans

Low default risk

Cash

Deposits Bank

BorrowerBalance Sheet:Loans

Low default risk

Cash

SPV(CDO, CMBS, etc.)

Cash

Cash

Credit &Counterpartyrisk

Cash

Credit &Counterpartyrisk

Investors

Originate to hold

Originate to distribute

Asset flows

Step 2

Loan warehousing

Credittransformation

(blending)

Credit, maturity,and liquidity

transformation

Credittransformation

(blending)


transformation

Maturity andliquidity

transformation

ABSissuance

ABSwarehousing

ABS CDOissuance

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transformation

Wholesalefunding

Step 3 Step 4 Step 5 Step 6 Step 7

Funding flows

Loans ABS ABS ABS CDO ABCP

ABCP Repo ABCP, repo CP, repo ABCP repo

Loans $1 NAV

Figure 7: Business model

Figure 8: Complexity of asset/funding flows, (Source: Adapted from Pozsar et al. 2010)

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could then be sold to global investors. By June, 2008 Moody’s had downgraded 90 percent of all asset backed CDO invest-ments issued in 2006 and 2007, including 85 percent of the debt originally rated AAA, according to Lucas of UBS Securities. S&P reduced 84 percent of the CDO tranches it rated, including 76 percent of all AAAs.The experiences of the crisis and the numerous bank bail outs by governments, finally culminating in bail outs of different Eu-ropean countries, led to an increase and strengthening of reg-ulatory frameworks around the world. The G20 reshaped their process for regulating financial markets and banking institu-tions, adopting an even more stringent approach. The common Basel III was extended by the CRD IV package (including also CRR - Capital Requirements Regulation); new proposals for de-rivatives like EMIR were developed over the past 12 month; the Bank Recovery and Resolution (BRR) Directive started in 2013 and the Liikanen Plan was delivered by a High-level Expert Group by October 2012.The overall target is to disentangle the troubled banking sys-tem from the interrelated sovereign debt crisis. A decoupling is required of the linkage which currently exists between the

Given the diversity of existing business models in terms of size and complexity, it is not possible to define a best practice bank in terms of a generic business model and risk framework. And as banks are still in the process of finding a way to mitigate the pressure driven by greater regulation, increased competition and higher costs/lower profits, it is unclear with today’s knowledge how these business model innovations will look. But we can define a list of relevant key principles as guidelines for trans-formed business models by taking into account the mistakes of recent history as well as the challenges of the future. In chapter 7 of the research study we will show that these key principles are supported by both the literature and results of the empirical study. To achieve this we will start with an abstract principle by remembering that all banks are financial intermediaries:

Principle 1 (role as financial intermediary): A bank is a best practice institution if the organizational set up and technical framework enables the bank to play their business role as fi-nancial intermediary by optimal management and monitoring of information asymmetries.Monitoring of a borrower by a bank refers to collection of infor-mation before and after a loan is granted, including screening of loan applications, examining the borrower’s ongoing credit-worthiness, and ensuring that the borrower adheres to the terms of the contract. A bank often has privileged information in this process if it operates the client’s current account and can observe the flows of income and expenditure. This is most relevant in the case of small and medium enterprises and is linked to the bank’s role in the payments system (Wambugu and Ngugi 2013, p. 473).The ability to raise bank loans serves as a positive signal if the borrower subsequently seeks funds from capital markets. Even for the traditional core business of banks, delivering lending products to clients, the core competence is to manage informa-tion flows between issuers and investors. Even though the main symptoms of the crisis are connected with excessive indebtedness and high shares of financial insti-tutions in the world’s GDP, we do not believe that part of the ideal resolution of the crisis will be for banks to roll back their business models from “Originate to Distribute” to the tradition-al “Originate to Hold” business model. New capital definition and new capital buffers, new ALM ratios and new counterparty RWAs will reduce banks’ capacity to lend and will change banks’ funding and asset composition.Since, in the future, the equilibrium price of credit will be a function of several main factors like the risk/return-profile of the financed business target but also by the cost of capital and the cost of liquidity, we believe that “Originate to Distribute 2.0” will be the next business model for banks. In our view, banks will even act increasingly as financial inter-mediaries rather than as final risk takers. Even though it is not exactly clear from today’s perspective how this will look, the new Basel III securitization rules are a step in this direction. We believe that banks will also play the role of the most important financial intermediaries, but given reduced lending capacities they will have to share the burden of credit risk with other parts of the financial markets, like the so called real money accounts (insurance or asset management industry). New regulatory rules

Capital Requirements Directive (Press release CRD 2013)” Bank Recovery and Resolution Directive (BRR 2013) Report of a High-level Expert Group for possible reforms to the structure of the EU’s banking sector(Liikanen report 2012)

Greater Regulation

Higher competition

Increasing custumer demand

Higher costof risk

Eroding profits

Future growthand sustaina -

bility

Differentiateto survive

Pressure Costs/Profits Inovation

Figure 9: Challenging environment

sovereign ratings and the credit ratings of their banks. This linkage comes from the so called triangle situation between Governments, Central Banks and Commercial Banks. The exces-sive focus on government securities as the core of the liquidity reserve, as well as collateral for derivative transactions (both OTC and centrally cleared), creates an inherent linkage between bank debt and sovereign debt, which is due to the special status the latter is granted in the determination of regulatory capi-tal requirements. Therefore, the EU banking union is going to be based upon the pillars of (additional) Europe-wide banking supervision, deposit insurance and a bank restructuring fund.In short, pressure in the form of greater regulation, higher com-petition and increasing customer demand led to higher costs of risk (capital) and eroding profits which can only be handled by innovation (figure 9).

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to avoid risk arbitrage and adverse selection will force banks to share all relevant data with co-investors to enable execution of their own due diligence processes. As a consequence, banks will have to cover core functions as providers of risk data and risk management services for their clients in the future. This will force banks to re-engineer their processes in order to improve response times to clients and to allow a more rapid reaction to market developments. Improved streamlining and standard-ization of data management processes, new technologies for enabling improvements in banks’ ability to react better and faster to their customer’s needs, and enhanced client servicing platforms offering clients real-time data to manage their credit exposure will be complementary factors of success in the future. Furthermore, data management and provision for third parties will be a dominating activity of financial intermediaries.We will summarize this discussion in a second principle for being best practice:

Principle 2 (use of financial innovations): A best practice bank will use also financial innovations for risk transfer to fulfill their role as key member of different financial intermediation chains. The related task to manage funding, asset and information flows has to be supported by a technical framework which is delivering full transparency for risk management departments, external and internal clients, and supervisory authorities.Driven by Basel III, the banks’ balance sheets will become smaller. Moving forward, it will be crucial for banks to diversify income streams from pure interest earnings. Especially for business with corporates, it becomes more and more difficult to separate oth-er services from the traditional lending function. Nevertheless, non-interest income streams are much more volatile than interest earnings and banks will also face the two-sided problem of fall-ing asset prices and eroding funding sources. At the same time, information flows in the global financial markets become bigger and faster, making large, short term movements of key market data more probable. Moreover, it will become crucial to perma-nently improve the information flows inside the bank between front office departments, risk units, and senior management. In this sense, IT innovations will become the twin of financial inter-mediation and a key competence for institutions with business models related to the management of information asymmetries.

Principle 3 (risk & profitability): A best practice bank has a de-tailed and contemporary view on the relationship of their Risk Bearing Capacity on one hand and their profitability on the other. Best practice is to use a state of the art technical framework which takes into account the opportunities of technical inno-vations to permanently improve the timeliness and detail of all relevant information regarding risk and profitability. Besides showing how principles 1 – 3 can serve as axioms for the modern banking business, we want to highlight that the detailed definition of the meaning of “contemporary” and “detailed” de-pends on the size and complexity of the business model of the bank and its level of system relevance. That is also the regulatory supervisory view given the principle of double proportionality between ICAAP and the Supervisory Review Process as defined in Pillar 2 of the Basel framework.

The focus of the regulators is to reduce the volatility of banks’ profitability by income stream diversification and limitation of proprietary trading (USA: Volcker’s Rule). Volatility in combina-tion with interconnectedness with other financial institutions and high leverage are the fundamental reasons for the system relevance of banks. The macro prudential view of supervisors on the financial networks leads them to focus on identification and effective limitation of sources for systemic risks in banks’ business models.More important than a dual system of investment banking and commercial banking from a supervisory perspective, is the mit-igation of the “too-big-to-fail” problem. A main target of the supervisors is the development of harmonized cross border reso-lution mechanisms. So based on actual political discussions and supported by the requirements of supervisors and tax payers, we believe that the next principle has a self-explanatory status.

Principle 4 (market exit & living wills & resolution): The techno-logical and organizational framework for reporting fulfills all re-quirements to deliver supervisory authorities, a comprehensive understanding and analysis of complex internal and external issues of the relevant bank, facilitated by an immediate access to all relevant details necessary for a credible market exit scenario.

Principle 5 (data and process management): Best Practice is to manage the information and processes required for account-ing, solvency capital calculations, treasury operations and risk, liquidity and funding management purposes in a common and consistent database for all regulatory and risk reporting require-ments.We have already discussed the fundamental issue that the pre-crisis Originate-To-Distribute business model transformed long term credit risk into short term liquidity risk. In the future, the risk of a combination of bank runs with eroding asset prices will also be a major risk. It is essential for banking organizations to view liquidity risk and funding management as an integral part of their long-term enterprise strategy.

This leads us to the next best practice principle regarding liquidity and funding:

Principle 6 (liquidity & funding & collateral management):

(i) The funding base of a best practice bank is complementary to their business model

(ii) Dependent on the size and complexity of their business model a best practice bank has all relevant technological requirements available for a contemporary and detailed monitoring of the alignment of the asset and liability side of their balance sheet.

(iii) Dependent on the size and complexity of their business model a best practice bank has all relevant technological require-ments available for real-time monitoring, forecasting and scenario simulation of relevant liquidity measures and ratios.

(iv) A best practice bank monitors the availability of their funding sources and their significant impact on the risk profile of the organization on at least a daily basis.

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(v) The technological framework of a best practice bans ensures regulatory compliance: Basel III key figure calculation and sim-ulation coupled with comprehensive liquidity risk reporting.

(vi) A best practice bank has technological capabilities available to achieve effective enterprise wide collateral management

(v) The liquidity, funding, and collateral management infra-structure of a best practice bank has to ensure that the senior management has at any time and from anywhere, fast and accurate access to all relevant risk figures including liquidity risk appetite of Key Operating Entities (KOE), stress test results of KOE and liquidity limits, indicators and met-rics of KOE. Further, best practice is to implement existing technological opportunities to minimize response time to all senior management requests regarding liquidity & funding risk related data and analytics.

(vi) Best practice banks have an advanced early liquidity risk warn-ing system in place linked to several risk indicators.Since classic risk management tools and frameworks failed to prevent the recent financial crisis, we face the requirement to move from a micro prudential to a macro prudential risk management ap-proach and to a new risk management culture. New require-ments include the calculation of regulatory capital for the mar-ket value of counterparty credit risk (Credit Value Adjustment) requiring an integrated look on different risk categories (Credit Risk and Market Risk) based on a unified data structure. Chang-ing market environments such as the emergence of significant differences between LIBOR/EURIBOR and OIS-rates require new valuation set ups for financial instruments (multi-curve valuations). Generally, the purpose of risk management is a key competitive factor and the best practice use of risk manage-ment is to increase shareholder value.

Principle 7 (risk management & capital management & valuation):

(i) Regulatory, Risk Management and Business processes in a best practice bank must run together and on the same in-formation basis.

(ii) A best practice bank monitors its capital structure on a reg-ular basis. In case of correlated shifts of relevant risk fac-tors, a best practice bank is able to calculate the impact on regulatory capital demand and economic capital demand, on a group level and for business areas or segments on a contemporary basis.

(iii) A best practice bank has an integrated view on all business relevant risk categories (Market, Credit, Operational Risk, etc.) supported by a harmonized framework including a uni-fied data warehouse. This unified data warehouse contains all data regarding relevant risk types including product spe-cific data and legal entity views.

iv) A best practice bank has implemented state of the art valu-ation procedures and risk analytics taking into account the existing structure and availability of input data (for example: product valuations in a multi curve environment).

(v) Best practice regarding valuation procedures and analytics is the introduction of highly automated processes enabling decision makers to identify risk return profiles of products and counterparty relationships.

(vi) A best practice bank has a powerful framework available for stress testing based on flexible and customized modules for automatic analysis of stress scenarios and ad hoc stress testing. Scenario calculations are based on timely balance sheet information. Stress testing capabilities specifically cover reverse stress tests, impact of wrong way risks and correlated shifts in systematic risk factors for ensuring a macro prudential view. The framework for stress analytics is designed to assess the impact of market dynamics on trading positions.

(vii) The risk management infrastructure of a best practice bank must ensure that the senior management has, at any time and from any place, fast and accurate access to all relevant risk figures. Furthermore, best practice is to implement ex-isting technological opportunities to minimize response time to all senior management requests regarding risk re-lated data and analytics.

(viii) Best practice banks have an advanced early risk warn-ing system in place linked to several risk indicators. Pre-crisis, many banks built up exposure on the banking book in complex transactions related to market risk and credit risk factors which they could not cover with their existing models and risk frameworks. The ability of a bank to play the role of risk taker by involving banking book and balance sheets capacities is very often a competitive factor and crucial for some kinds of business models. As a conse-quence, an increasing number of banks require advanced methods to measure and manage their risk on the banking book. In the past, the risk framework of a bank was very often not able to deliver a correlated view of all relevant risk factors in time and as part of a highly automated process. An advanced technical framework for risk assessment on the banking book will assist in meeting the high expectations of demanding clients as well as more stringent regulatory requirements.

Principle 8 (portfolio management on the banking book):

(i) Best practice banks have advanced technical frameworks available at the portfolio level to simulate the various risk factors relevant to the portfolio while taking the various dependencies into account, in order to provide all relevant information for the assessment of portfolio risk including the necessary data to run hedging strategies against se-lected risk factors. These calculations should be at a highly automated level.

(ii) The timeliness and desired degree of detail of the infor-mation above depends on the size and complexity of the banking book portfolio and the business model of the bank.

(iii) In addition to share and commodity prices, exchange rates and interest curves, major risk factors include, above all, the spread curves that describe default probabilities and the volatility surfaces that describe market dynamics.

(iv) An essential element in the modeling of common risk factors is the assumption of distributions more appropriate than the normal distribution, in order to take the “fat tails” observable in the real markets into account.

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(v) In the design of systems, a clear distinction should be made between systems that store information (product, risk data, finance data) and systems that do calculations (risk engines, finance calculations, product valuations). Calculation results should again be stored in the readily accessible data ware-house.

(vi) Trading book processes should be applied to the banking book with adequately reduced frequency and data require-ments to keep costs at bay.

In order to rebuild trust and confidence with clients, regulatory authorities and politicians, it is very important for banks to pro-tect their business models and activities from the consequences of criminal actions. For the detection and analysis of fraudulent transactions, recent advances in statistical pattern recognition models, combined with advanced text and image processing methods, have proven very rewarding. Clustering procedures, for example, can be used to group large numbers of mutually similar transactions together, so that the sudden occurrence of material behavioral deviations from previously observed patterns can trigger the activation of a warning signal. Best practice banks will use all these advances to implement maximum protection against fraudulent transactions to the fullest extent possible.

Principle 9 (fraud detection, analysis, and prevention):Best Practice Banks implement state of the art technical frame-works to

- identify fraudulent behavior before (significant) losses occur,- keep step with rapidly changing behavioral patterns in this field,- reduce the frequency of “false alarms”, - speed up and improve the efficiency of fraud detection and

prevention activities through automation, and- minimize any unwanted impacts on the core business from

fraud-related activities.

From a senior management perspective, there is full responsi-bility and personal liability for business strategy and the cor-responding risk strategy of the bank. During the intellectual process for understanding the crisis, it became more and more clear that for many banks especially in the German speaking area the root of the problem was not too high Return on Equity (RoE) targets. Banks in Germany became risky institutions involved in many complex transactions without sufficient investment and risk management processes, as they had inadequate business models incapable of transforming their liquidity and risk capital resources into stable and profitable business. Also, from a fi-nancial intermediary perspective, managing the risk of financial intermediation chains is best understood as an integral part of a value-oriented corporate governance.Now we want to examine the principles by which a bank can leverage their role as financial intermediary for creating unique value with customers and for establishing a long term and sus-tainable business model. We cannot forecast from today’s per-spective how the range of financial services in different business models of banks will change, but we can define general princi-ples as to how banks can, on the basis of an existing range of

services in a specific client segment, generate stable returns in the long run and be successful by differentiating from their competitors. We will point out in chapter 7.1 the support from our key findings in the interviews, which demonstrates why we see the principle below as common sense and what can be viewed as best practice in this field.

Principle 10 (creating unique values with clients: client centricity and effective use of distribution channels):

(i) Best practice banks are investing in advanced technical ap-plications for modern distribution channels that enable cus-tomers to conduct of a large variety of banking transactions “on the go”.

(ii) To reduce the degree of complexity for clients, best practice banks will synchronize traditional and new banking channels to ensure that –

- Banks request the same piece of information from a custom-er no more than once.

- Banks can retrieve all existing relevant information when-ever the customer comes into contact with the bank.

- Banks can recognize the customer’s demands in a rapid and reliable manner, and foster a more personalized customer experience.

(iii) Best practice is the use of information technology for the strategic purpose of re-designing bank branches in an opti-mal manner.

(iv) Best practice is the use of information technology to facili-tate organizational learning in order to offer superior advi-sory capabilities.

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Main topics for desk research: Key driver of changes in the banking industry | Banking Study

5.1 Changes in the Regulatory Framework5.1.1 The Dodd Frank ActThe Dodd Frank Wall Street Reform and Consumer Protection Act (Public Law 111-203 – July 21, 2010) is a U.S. federal law enacted in reaction to the recent worldwide financial crisis. It owes its name to Senator Chris Dodd and Congressman Barney Frank, who jointly created it. According to its preamble, its main objectives are “to promote the financial stability of the United States by improving accountability and transparency in the fi-nancial system”, to end ‘‘too big to fail’’, “to protect the American taxpayer by ending bailouts” and “to protect consumers from abusive financial services practices”. The Senate Committee on Banking, Housing, and Urban Affairs (Senate Committee on Banking 2010, p.1) summarizes the high-lights of the new bill as follows:

• Consumer Protection with Authority and Independence: The new bill creates a new independent watchdog, housed at the Federal Reserve, with the authority to ensure American consumers are getting the clear, accurate information they need to shop for mortgages, credit cards and other financial products, and protects them from hidden fees, abusive terms and deceptive practices.

• End “Too Big to Fail” Bailouts: The bill eliminates the pos-sibility of taxpayers being asked to write a check to bail out financial firms that threaten the economy. It does so by cre-ating a safe way to liquidate failed financial firms, imposing tough new capital and leverage requirements that make it undesirable to increase balance sheets tremendously, up-dating the Fed’s authority to allow system wide support but no longer prop up individual firms and establishing rigorous standards and supervision to protect the economy and Amer-ican consumers, investors and businesses.

• Advance Warning System: The new bill creates a council to identify and address systemic risks posed by large, complex companies, products and activities before they threaten the stability of the economy.

• Transparency & Accountability for Exotic Instruments: The new bill eliminates loopholes that allow risky and abusive practices to go unnoticed and unregulated – including loop-holes for over-the-counter derivatives, asset-backed securi-ties, hedge funds, mortgage brokers and payday lenders.

• Federal Bank Supervision: The new bill streamlines bank supervision to create clarity and accountability. It protects the dual banking system that supports community banks.

• Executive Compensation and Corporate Governance: The new bill provides shareholders with the opportunity to in-fluence pay and corporate affairs with a non-binding vote on executive compensation.

• Investor Protection: The new bill provides stronger new rules for transparency and accountability for credit-rating agencies to protect investors and businesses.

• Regulation Enforcement on Banking Books: The new bill strengthens oversight and empowers regulators to aggres-sively pursue financial fraud, conflicts of interest, and ma-nipulation of the system that benefit from special interests at the expense of American families and businesses.

5.1.2 Changes in Regulation and Banking Supervision: Basel III As can be inferred from the related publications of the Basel Committee on Banking Supervision (Basel Committee on Banking Supervision 2010, 2011), the main characteristics of the new Basel III framework for banks and banking systems include the following:

• An enhancement of banks’ capital bases through increased capital requirements, more rigorous capital standards and the mandatory build-up of capital buffers;

• More stringent standards for counterparty credit expo-sures arising from banks’ derivatives, repo and securi-ties-financing transactions;

• New provisions on liquidity management and monitoring; and

• A strict limitation to the build-up of leverage as a safe-guard against the underestimation of risks due to inade-quate models or model inputs.

The new global liquidity standards will demand that banks focus more strongly on the acquisition and repetition of cus-tomer deposits and lower customers’ dependence on other forms of short-term funding (e.g. interbank lending), especially for those customers for whom maturity transformation con-tinues to be a main source of income (Gomes 2013, p. 43). Furthermore, banks will have to hold a larger share of their respective asset bases in the form of instruments that are stable in value and can be turned into cash at short notice (Gomes 2013, p. 39). Banks or corporations can seek to recon-cile the need for stable funding with the goal of profiting from term transformation, which can be done by either issuing or synthetically creating long-dated floating rate debt; a point which been raised by several authors (Faulkender 2005) and (Vickery 2008). Our supposition, that credit securitization will remain an important source of funding (and capital relief) for many institutions, is supported, inter alia, by the reflections of Akseli (Akseli 2013) and the observations of Bechthold (Bech-told 2012). On the other hand, research by Härle (Härle 2010 p. 11–12) strongly supports our expectation that the new rules applying to this field and greater risk awareness on the side

5 MAIN TOPICS FOR DESK RESEARCH: KEY DRIVER OF CHANGES IN THE BANKING INDUSTRY

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of investors will strengthen the transparency requirements for such products and require originators to retain a larger stake in related transactions.Particularly in over-the-counter (OTC) derivatives trading, the joint occurrence of time-varying counterparty credit quality and exposure and the presence of “wrong-way risk”, i.e. the possibility of a negative correlation between both, currently command a high level of attention (Liu 2013). The calcula-tion of a corresponding indicator, the Credit Value Adjustment (CVA) has become part of the mandatory regulatory capital calculation under Basel III. For banks with considerable OTC derivatives exposure, effectively controlling the often highly volatile quantity and hedging against unwanted risks is a for-midable task. It usually involves the aggregation of information from a variety of asset class-specific trading systems used with different sub-portfolios on a daily basis in real time and hence constitutes a major operational and technological challenge (Delarue and Siddiqi 2013). For banks with high-volume trading desks intending to tackle this challenge, procedures capable of allocating computational demands to multiple processors will be of great benefit (Stops 2013). By allowing a faster processing of batch jobs, they will be able to supply decision makers with ex-ante information on possible transactions and help them assess the likely implications for capital requirements. The attainment of this goal, however, necessitates the consistent coupling of data from the bank’s risk management and trading operations. In more general terms, the tasks of adequately assessing the probability and severity of rare, high-impact “tail” events and realistically aggregating risk contributions from different sources allowing for nonlinearities in their dependency struc-tures continue to be at the center of interest for practice leaders in banking and supervisory authorities alike. This is evidenced by a recent whitepaper from Moody’s Analytics (Stuart and O´Connor 2013). The failures of the traditional Value-at-Risk to capture events beyond the confidence level have prompt-ed calls for a supplementation or replacement by Expected Shortfall. This number describes the statistically expected loss occurring if the threshold is actually exceeded (Yamai 2004). Extreme value theory, a branch of statistics focusing on very large deviations from the mid-point of frequency distributions, has made important contributions to the estimation of this measure in practice (Gilli and Kellezi 2006).Given the large amount of time and resources banks invest in the building and calibration of risk models, it must not be forgotten that the ongoing validation of these models based on observed data is an equally important task. Model valida-tion essentially consists of the ex-post comparison of ex-ante predictions and observed values of the variables of interest, and involves statistical appraisals of whether the deviations between the two are small enough to be considered random or so large that they call for a re-parameterization or reformula-tion of the model (International KPMG 2006). Performing this assessment is often anything but trivial since it may involve a large number of resampling rounds in order to produce valid uncertainty margins for the model output.

It is estimated that a growth of global data by 40% annualized, which would lead to 44 times the volume of data by 2020.

5.1.3 Multi-Curve ValuationIn the field of derivative valuation, financial institutions tra-ditionally used a single standard yield curve for discounting future cash flows and deriving forward rates. This approach im-plies that all participants in the market have the same amount of credit risk, that the firm could obtain funding at standard money market rates (LIBOR/EURIBOR etc.), and that the cred-it risk pertaining to yields for different maturities was small enough to be neglected for calculation purposes. Experience gathered during the most recent financial crisis has, however, put forth clear evidence that assuming an equal credit risk for all market participants cannot be sustained. This point can be exemplified by two cases (Samborn 2011):The spread between LIBOR rates and overnight indexed swap (OIS) rates for the same maturity widened dramatically in the aftermath of the collapse of Lehman Brothers (Sengupta and Tam 2008). Because an OIS does not require an exchange of principal, the corresponding rates are regarded as nearly risk-free, so that the LIBOR-OIS spread can be reasonably regard-ed as a strong indicator for the relative stress in the money markets, meaning that a higher spread is an indication of a decreased willingness to lend by major banks (Brown and Finch 2009).

• The spreads on single currency basis swaps involving mon-ey market rates of different maturities, which used to be negligible prior to the crisis, also widened sharply. In order to adequately mirror the conditions of unequal credit risk when valuing derivatives, market participants ought to use different curves for discounting on the one hand and for projecting future money market rates on the other.

• A first set of curves, which can be referred to as the “ac-crued curves”, is used to derive forward rates for different coupon frequencies. When valuing a swap with quarterly payments, the implied forward rates for valuing the float-ing leg should be calculated using an accrued curve based on three-month LIBOR/EURIBOR.

• Another different curve is used to calculate the present value of all future cash flows. It should be ensured that two iden-tical cash flows occurring at the same date are assigned the same present value. To date, there is no standard definition of the exact nature of the curve to be used for discounting.

• When valuing positions that are subject to collateralization, it seems plausible to use overnight index swap rates based, e.g., on EONIA, because default risk appears to be negligible.

• In all other cases, constructing the discount curve on the

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basis of very liquid instruments (e.g. swap rates) seems appropriate. Bloomberg, for example, uses 6-month-EURI-BOR-based swap rates for the Eurozone and 3-month-LI-BOR-based swap rates for the U.S. as standards.

5.2 Developments in the Technology Environment5.2.1 Cloud Computing In many areas of the banking business and particularly in the fields of risk management and regulatory compliance, a key con-cern for decision makers is the ability of IT systems to handle an increasing amount of information in a performance and cost-ef-ficient way. One concept that shows considerable potential in this context is cloud computing. According to the U.S. National Institute of Standards and Technology (Mell and Grance 2011), “cloud computing is a model for enabling ubiquitous, conve-nient, on-demand network access to a shared pool of config-urable computing resources (e.g. networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.”The main ways in which cloud computing can help financial in-stitutions improve their business can be summarized as follows (Nikam et al. 2012; Christmann and Falkner 2011):

• The application of cloud computing releases users from the necessity to operate the corresponding facilities locally and on their own, enabling them to pick and choose services from one or more providers as needed.

• The enhanced flexibility supports a faster development of new products and enables a swifter response to new de-mands from outside the organization.

• Cloud computing enables an organization to exchange a huge, upfront capital expenditure for smaller, ongoing op-erational charges as it does not require any large ex-ante investments in new hard- and software.

• Given that the responsibility for operating the technology rests with the provider, using cloud services can enable banks to achieve a high level of data protection and fault tolerance, as well as improved back-up and disaster recov-ery facilities at reasonable costs. It thus enables an organi-zation to focus more exclusively on its core business rather than dealing with IT-related details.

While outsourcing IT operations to the cloud, it should be kept in mind that fully realizing these potential benefits requires a high degree of reliability from the provider.

By outsourcing IT operations to the cloud, many, only mod-erately efficient and potentially underutilized computer centers and server rooms can be replaced by a few, highly optimized computer centers which are operated in a par-ticularly energy-efficient manner. This is likely to reduce energy costs and the carbon footprint of the organization. It should be kept in mind that fully realizing these potential benefits requires a high degree of reliability from the provider. Organizations seeking to move some of their IT operations to the cloud are strongly recommended not to base their provider selection on cost savings alone, but to look for a partner with clear evidence of comprehensive expertise in the management of enterprise data processing centers. Suppliers must give highest priority to data security (e.g. by encrypting all stored and transmitted data) and data integrity, have a proven ability to withstand denial-of-service, virus, and malware attacks from outside, and boast a record of very high availability (e.g. > 99.9% during working days) as well as a watertight disaster recovery plan. A clear process of identifying problems and developing resolutions must be in place, and the service-level agreement between client and provider must cover all important details about availability, customer support, response times, and per-formance benchmarks (Trappler 2010). From a regulatory point of view, cloud computing is a form of outsourcing. As a consequence, the same supervisory require-ments that apply to “traditional” forms of outsourcing also apply here. Banks using cloud computing services are obliged to un-dertake a comprehensive due diligence of all related elements (Olaoye 2012). This involves carrying out an identification and assessment of the nature, scope, complexity and risk content of all activities and processes entrusted to external providers. Particular attention is required in cases where processes related to the fulfillment of the risk measurement and reporting duties prescribed under the Basel rules are dealt with. The legal re-sponsibility for the timely, complete, and accurate performance of these activities necessarily remains with the bank, since risk management is a core business activity that cannot be entrusted to an outside party. As a consequence, the use of cloud comput-ing will require the bank to monitor these processes closely and regularly to ensure their conformity to regulatory provisions. Moreover, outsourcing must not restrict the relevant bank su-pervisors in the performance of their duties (Basel Committee on Banking Supervision 2005). 5.2.2 Big Data Big Data has been used very often in recent years. The develop-ment of the internet and the upcoming of social media have mas-sively increased the overall amount of data that can be used for business. It is estimated that today the amount of data generated every 12 hours is as much as it was from the start of humanity until 2003 (SAP/FCW 2013). McKinsey Global Institute estimated in their “Big Data” field study in 2011 a growth of global data by 40% annualized, which would lead to 44 times the volume of data by 2020 (McKinsey Global Institute 2011, p. 16). Obviously, the speed of generating data is increasing exponentially and in an unstructured format, which means it does not reside in fixed fields, e.g. free-form text, as in the body of emails. This is

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a problem as the majority of business solutions need structured data (SAP/FCW 2013) like relational databases or spreadsheets. Traditionally, companies based their business decisions on trans-actional data (structured) stored in databases but today most data is non-traditional (not structured) and can be found, for example, in weblogs or social media. Technological progress has made the storage of data and computing capacity much cheaper and has opened the possibility for collecting any potentially interesting data (Dijcks 2013, p. 2). In general, big data includes and can be clustered into:

• Traditional enterprise data, e.g. customer information • Machine-generated /sensor data, e.g. trading systems data• Social data, e.g. twitter blogs, Facebook

Big Data is not only a matter of size but also of velocity, vari-ety and value. Twitter, for example, produces social media data streams of over 8 TB per day and this information facilitates valuable connectivity for a better customer relationship (Dijcks 2013, p. 3). The challenge is to find useful information within this large amount of data. IT is the only way to fulfill this task and therefore is essential for future business.

5.2.3 The Importance of Mobile Technology and Social Media Mobile banking, i.e. the performance of account transactions, payments, credit applications and other banking transactions through a mobile device, has experienced fast growth globally (Bećirović et al. 2011). The Portio Research Mobile Factbook 2013 (Portio Research Ltd. 2013) predicts that the worldwide mobile subscriber base amounted to nearly 6 billion by the end of 2011 and can be expected to experience a compound annual growth rate of more than 7% in the time span 2013–2016, with markets in Asia/Pacific and Africa leading the way. It seems justified to assume that mobile banking, coupled with micro-fi-nance, is one of the great trends that will shape the future of the financial services industry in emerging economies.In the take-off phase of mobile banking that many emerging economies currently experience, the main emphasis is on en-abling access to the most elementary functionalities offered by mobile banking systems, which can be summarized as follows (Bećirović et al. 2011, p. 91):

1. Accumulation of currency in accounts that can be accessed using mobile devices.

2. Conversion of cash into and out of the stored value account. This may be achieved by visiting a bank branch, a retail store of the mobile network provider, or even an independent retailer who works as an agent for the transaction system.

3. Transfer of currency between accounts using mobiles, e.g. via SMS.

It should be obvious from these findings that accuracy of infor-mation provided, the speed and reliability of services delivered, and their 24/7 availability are key success factors for financial institutions wanting to participate in the projected growth of this market segment.In much of the industrialized world, where the nearly ubiquitous prevalence of mobile devices sets a limit to further growth in the

subscriber base, qualitative changes in the technological capa-bilities and the usage patterns of mobile devices are among the most important factors calling for attention by decision makers in banking. The continual integration of mobile and web-based tools and processes along with highly interactive online communication strongly impacts the way banks conduct their business. Both businesses and private citizens have increasingly opened up to the opportunities created by IT innovations. They use mobile phones, interactive digital devices and social net-works to share and find out which companies they deem to be best, reliable and trustworthy and which products to buy, and they often even use social media to let others know about their customer experience (Bansal 2013). By intensifying the commu-nication with customers, banks also get relevant information to improve their product and service portfolios.

Twitter produces social me-dia data streams of over 8 TB per day and this information facilitates valuable connec-tivity for a better customer relationship.

A large number of banks have made considerable efforts to provide web-based functionalities for mobile computers and smartphones, putting customers in a position to perform a large multitude of transactions wherever there is a mobile connection. While a considerable number of banks already use social me-dia as an engagement tool, some of them have recently begun to market their products and services through these channels with the help of targeted advertising techniques, website traffic analytics and conversion rate measures to gain new insights into the preferences and behavioral patterns of customers (see Camhi 2013a). At the same time, it has to be kept in mind that the mere use of technology in isolation does not automatically create value. Rather, the significant challenge is to employ these instruments in a way that improves the customer experience. In this context, three key drivers of success arise:The first one is the seamless integration of new and pre-existing platforms and channels: The variety of banking channels and platforms has undergone a rapid expansion. As this trend is likely to continue, processes are going to become increasingly contexts. Banks will need to enhance their back office support systems in order to make sure that customers are served with the same high quality standard regardless of whether they ap-proach the bank through a “traditional” or “new” communication channel (Hamprecht and Brunier 2011). Ideally, a client advisor will never need to ask for the same customer-related information twice, because the bank’s customer relationship management

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system is powerful and reliable enough to provide instant ac-cess to all relevant details. This greatly enhances the speed and accuracy with which the bank realizes customer needs, and en-ables a greater degree of personalization in product and service offerings to customers (Stine 2013).The second driver of success is the reshaping of branches net-works. Until recently, the main focus in the use of IT within banks was on cost-cutting: Customers were incentivized to conduct transactions via the internet, using mobile end-user devices, and self-service terminals, and once these measures had become effective, many branches were closed down. Yet at the same time, the remarkable progress in technology cannot obscure the fact that most customers in need of expert advice on more complex issues, like company financing, real estate purchases, asset allocation or old age provision) still turn to client advisors at the local bank branch for support (Vater et al. 2012). Hence, some have chosen to reshape their branch networks in the form of a hub and spoke structure. A few attractively designed and centrally located pivotal branches provide the full range of bank offerings, whereas several smaller, peripheral outlets support customers with standardized products and services (see Econo-mist 2012; Accenture 2012, p. 5). In thinly populated geograph-ical regions, where the mere distance between a customer’s place of residence and the nearest suitable bank branch hampers the accessibility of individualized services, some banks use of videoconferencing equipment to bridge the distance, and en-able customers to schedule consultation appointments via the web (Camhi 2013b). These linkages of traditional and innovative distribution channels can make a significant contribution to rec-onciling the goals of cost efficiency and proximity to customers.The third driver of success is to improve the organization’s learn-ing capacity through the use of technology. The World Wide Web has greatly improved the availability of information on financial markets, products, and services. As a consequence, many cus-tomers have achieved a high degree of financial literacy and expect banks to supply them individualized, best-in-class advice for the attainment of their financial goals. The superior advisory capabilities demanded by customers (see Vater et al. 2012, p. 6) put strenuous demands on the expertise, the communicative competence, and the media literacy of banking staff. One way in which banks can cope with this challenge is to use interac-tive learning platforms and information management systems to make sure that the scarce resource of expert knowledge is put to the best possible use. The arrival and rapid further development of highly interactive, web-enabled social media have fundamentally changed and en-riched the modes of communication in society, thus being both an enabler and a transmitter of economic and societal change (Garst 2013; Leadbeater 2013). For banks aspiring a high degree of customer centricity, today’s internet greatly enhances the precision with which advertising campaigns can be targeted and product can be tailored to fit customer needs. Customers familiar with the capabilities of the “Web 2.0” accumulate in-formation, exchange views, and express opinions about bank offerings online. The members of this increasingly self-confident and demanding customer group often want banks to engage in truly mutual communication with them – not exclusively, but

also via social networks (Bansal 2013). For banks that succeed in building and maintaining a high degree of competence in dealing with this situation, the ongoing “social media revolution” opens up great opportunities for individually tailored offerings to customers at reasonable cost. Combining data from internal sources with information made available on the web is another highly promising way of gaining insights into the preferences, attitudes, and behavioral patterns of customers. Yet the way to the attainment of this goal is not an easy one: Both the data released online and in connection with financial transactions come in unparalleled quantities and at enormous speed, lack a common structure or format, take their origin from several heterogeneous sources and may quickly be-come outdated (see Nair et al. 2012, p. 8). The database systems and statistical software packages currently in use often simply cannot deal with this situation quickly enough (Snijders et al. 2012). Only very recently though, scientists and technicians have made significant advancements in developing software than can utilize a very large number of processors and work on several servers at the same time, thus dramatically reducing the time requirements of such highly complex computations. The simul-taneous performance of numerous database queries, too, has now become possible (Boja et al. 2012). In conjunction with the momentous progress made in the areas of artificial intelligence and machine learning, this has spurred many highly innovative applications, e.g. the detection of hidden patterns, the investi-gation of previously undetected connections (Rouse 2012), the early discovery of possible future trends (Yurcan 2013) and the graphical representation of analytical results in a way that facil-itates understanding by strongly appealing to intuition (Taylor 2013). Banks, in particular, can reap enormous rewards from these so-called “big data analytics”: Their application can, for example, help to assess the way in which account holders react to shifts in money market rates, identify customer groups particularly open to new product offers, and considerably enhance the precision rating and valuation models. Moreover, their ability to find and statistically describe complex dependencies between several fac-tors of influence can open up great potentials for the discovery cross selling opportunities (Baumgartner et al. 2012, p. 3). Yet on the part of banks, turning these opportunities into a source of sustainable added value also requires a great deal of awareness, and a careful management of the risks accompany-ing these technologies. Data must be effectively shielded from unauthorized access or alteration, misusage, illegitimate disclo-sure, and unintended loss or destruction, and banks must and establish reliable governance models to ensure legal compli-ance and mitigate reputational risk (Communications-Electron-ics Security Group 2012). As the pace of technological progress is likely to remain high, and future developments in both the legal framework and public opinion are hard to predict, coping with this challenge will continue to place high demands on busi-nesses both within and outside the financial sector.

5.2.4 In-Memory ComputingTraditionally, the random access memory (RAM) of a computer system is used as temporary storage for rather small quantities of data which have to be accessed very quickly. The sustained de-

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cline in the price of dynamic RAM chips and the strong improve-ments in their performance have led to a substantial increase in the quantities of data which can be stored in main memory (Fulton 2013). As a consequence, large datasets can now be stored in the main memory of dedicated servers, from which they can be retrieved at an extremely high speed (Janssen 2013). The practice of doing so is referred to as “in-memory computing”. The following graph, originated by information technology research and advisory firm Gartner, Inc., and reproduced by Elliott (Elliott 2013), summarizes its key characteristics:

In-memory computing has been applied mainly for analytical purposes. Moving a database into memory circumvents the time-consuming procedure of writing to and reading from physi-cal disks. This enables users to perform complex analytical tasks in real time and allows them to “slice and dice” huge sets of data with great flexibility and ease (Fulton 2013). In combination with the significant advancements that have taken place in the field of statistical data mining, this property can greatly enhance the ability of users to detect patterns in the data that would otherwise have been left undiscovered.

5.3 The Decisive Role of Mobile Technology for Banking in Africa Until recently, many people in African countries did not use ser-vices provided by the formal banking sector. Two main reasons

for this phenomenon are (Mhlaba 2012):• the high degree of income variability experienced by many

individuals,• the heavy transaction costs which impede many people

from using financial services.

The author further states that as a consequence, many people transfer cash physically to their intended recipient, and that it is not unusual for individuals to travel long distances in order to carry out financial transactions. Very often, persons who manage to find

employment in larger urban areas also rely on asking traveling friends or relatives to transport money to their families residing in more rural areas. Most “traditional” banks have branch networks that primarily cover urban areas and mainly target wealthy clients with regular incomes and higher payment amounts. In most African countries the transport infrastructure still re-quires a great deal of improvement, and the internet penetration rate is low by international standards (Mogale 2013). However, the percentage of Africans in possession of mobile phones now amounts to 60–70% of the total population (The Economist 2012). The main reason for this apparently lies in the fact that mobile phone penetration does not require the same level of infrastructure as other forms of technology (Dawson 2013). Thus, the arrival of banking-by-phone in Africa pioneered by the Kenyan mobile service provider Safaricom (Mhlaba 2012),

Figure 10: What is in-memory computing(Source: Adapted from Gartner 2012)

App. DataApplication

Code


Code


Code


Code

� 64-bit processors can address up to 16 exabytes of data� DRAM production costs drop by 32% every 12 months� 1 GB of NAND flash memory average price is 56$ cents*� Commodity hardware provide multi terabyte of DRAM� In-memory-enabling software is available and proven� IMC software is often embedded in products/services

In-memory Computing

WhyNow?

„Database of Record“

Main memory (DRAM)Main memory (DRAM)

Traditional Computing

„Database of Record“

� Persistency� Recovery� Post-processing� Backup

*Per Gartner‘s „Weekly Memory Pricing Index, 21 December 2012,“ G0024 7628

What is In-memory Computing?

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has the potential to provide new opportunities for growth and innovation throughout the economy. Four key mobile banking functionalities that are of particular relevance for African economies are (Ondiege 2010):

1. Mobile phones can serve as a virtual bank card. Information related to the customer (e.g. PIN and account numbers) and the service provider can be safely recorded on a mobile de-vice, allowing the latter to fulfill essentially the same func-tions as bank credit or debit cards.

2. Moreover, mobile phones can also be used to duplicate the functionalities of point of sale terminals. In this capacity, they can be used to communicate with the partnering financial institution in order to request authorization for transactions.

3. Mobiles phones can also be used as a substitute for automat-ic teller machines (ATMs). In this case, the respective points of sale do not only serve as distributors of nonfinancial goods and services, but also offer cash collection and distribution services.

4. To the extent that customers have reliable and affordable access to the internet as well as to mobile end-user devices with advanced computing capabilities, these devices can also be used as an Internet banking terminal. Apart from providing users with the possibility of immediate access to any account held with the corresponding bank and make payments and transfers from a distance, this will also facil-itate access to a wide area of other financial products and services, including, e.g. deposit accounts, micro-loans and micro-insurance contracts (Mulupi 2010).

Africa is home to some of the fastest-growing economies in the world and an emerging middle class (Wonnacott 2011). Therefore, it is reasonable to anticipate growth opportunities in many key industries, including financial services. However, the extent to which these hopes can be fulfilled depends crucial-ly on three necessary conditions (Kobo 2012). Firstly, security concerns regarding the vulnerability of mobile communication channels to cyber-crime, e.g. ATM skimming and the hacking of client accounts, must be addressed in a competent and trust-worthy manner. Secondly, the legal and regulatory framework will have to keep step with the risks and security requirements brought about with the advancement of technology and the rise of cross-border banking networks (Imara Africa Securities Team 2011). Finally, the financial literacy of customers must be enhanced to ensure that they can take advantage of new oppor-tunities offered and achieve sustainable economic benefits (Ke-fela 2011). These challenges are huge, but not insurmountable.

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In-Depth Interviews and Electronic Survey: Analysis and Key Findings | Banking Study

6.1 Main Trends in the Financial Industry: Results from In-Depth Interviews In our survey and during our interviews, a clear consensus pre-vailed that, as a senior executive of a U.S. bank maintained, “Changing regulatory requirements is the number one driver of business model changes.” This consensus includes the partici-pants from European and US banks of all sizes and business mod-els, as well as supervisory authorities and auditors. The above interviewee continued: “As regulation around capital, liquidity, leverage and market infrastructure is evolving, economics of many products and services are transformed and the business model needs to be adjusted to ensure sufficient returns.”However, risk management is by no means limited to the ful-fillment of regulatory standards alone. Instead, it is increasing-ly understood as has increasingly turned into a key business driver partner of competitive advantage. As Dr. Marc D. Grüter of Roland Berger Strategy Consultants put it, “there is a direct relationship between the quality – i.e. the effectiveness – of risk management, and the sustainability of profit development.” Ac-cording to this understanding, a bank’s Chief Risk Officer “needs to be closely involved in strategic decisions to clarify risk return profiles of products and business segments” as an expert from our group of interviewees maintained, which effectively puts a CRO into the position of a mediator between the CEO and those top-level executive responsible for market-oriented activities. Representatives from regulatory authorities and auditors, in particular, have clearly articulated the view that, in the words of a representative from a major global audit firm, “harmoni-zation of different regulatory requirements like IFRS, FinRep, CoRep, Basel III and BCBS 239 urges banks to reduce their data and reporting silos which is supported by new data warehouse technologies.” European and US supervisors as well as auditors have a common view that regulatory requirements in combina-tion with the bottleneck of limited access to relevant and timely data are the main challenge for banks in the coming years. When asked about how processes and technologies of banks should be designed in future, another senior expert from the audit pro-fession stated that “systems design should distinguish between systems that store data (product, risk data, and finance data) and systems that do calculations (risk engines, finance calculations, and product valuations)”, and added: “Front-to-back the same stored data should be used or calculation results should again be stored in the readily accessible data warehouse.” Along with centralized data warehouses, improvements in data and process governance, automated processes and flexible and customized modules for automatic analysis and stress scenarios were high-lighted as the most desired innovations for banks.

Auditors and supervisors mentioned that the existence of histor-ically grown, highly complex IT infrastructures in banks, which are based on different data silos that are not harmonized, is always the subject of intense discussions. This leads to consid-erable reporting time lags currently being accepted for metrics such as regulatory and economic capital usage at the consoli-dated group level, liquidity measures, changes in risk-bearing capacity, the use and exceeding of limits for market and credit risk, and change in the credit quality of large and million loans. According to a representative of a European banking supervisor, acceptable time delays today range between 5 and 10 days, but there is a clear expectation that “data availability and quality need to be improved together with the structure and trans-parency of risk reports to increase speed and accuracy of the group-wide reporting.”When asked in which parts of banks’ IT infrastructure she recognizes specific weaknesses, an export from a specialized consulting firm replied that “every reporting which combines data from different areas exposes weaknesses in the Banks IT infrastructure.” As a specific example, she mentioned the Euro-pean Banking Authority’s Financial Reporting Standard, FINREP, which combines accounting data and Basel III data. Even though there is a clear consensus that today’s accepted time delays for reporting will decrease in the future and banks will be forced to improve data availability and introduce flexible tools for automated processing, we got differing answers on what will be the acceptable time lags for capabilities of banks in calculating risk sensitive numbers. The expectations differ between participants, regulators and auditors as to whether system-relevant banks will have the processes and technologies in place capable to aggregate relevant risk factors like market or liquidity risks from different subunits or individuals on a group level, or whether they can deliver a dynamic, complete invest-ment picture that provides a correlated look across the risk-and-return spectrum of different asset classes in their banking books in real time. But even if real-time availability may not be required or is viewed as something that cannot be realized with existing technical possibilities, there is a common expectation that in the near future, the time frame deemed acceptable for the delivery of such information does not exceed one day.Beside the role of supporting increased regulatory and risk management requirements, technology is the biggest driver of change across all lines of business in the financial industry. “Data management, workflow and client/customer interaction are changing dramatically due to innovations in technology,” a banking technology expert interviewed for this study ascer-tained. Especially the interviewees from banks with a global business setup in Europe and the US, but also (to a lesser extent) the African participants, emphasized their assessment that the

6 IN-DEPTH INTERVIEWS AND ELECTRONIC SURVEY: ANALYSIS AND KEY FINDINGS

Source: Roland Berger Strategy Consultants, Press Release, Zurich, February 18, 2014.

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arrival of big data and real-time information and analytics con-stitutes a new era in information technology. There is a clear, common commonly held view that a competent handling of these issues will have many positive impacts on future business models of banks. A statement by a senior official from a British bank strongly confirms this perception: “Collecting, managing, and analyzing data has long been a core component of the bank-ing business. The availability of larger and more comprehensive data accompanied by the ability to deploy more powerful analyt-ical tools should allow us to make significant inroads in solving the most significant issues affecting our industry and deliver better service and opportunities to our customers.” The availability of more robust data and the development of real-time analytics will be beneficial for almost every part of the banking business. Harnessing big data gives opportunities to reduce costs and increase the transparency of operations for risk managers and supervisory authorities alike. Our findings suggest that there is widespread agreement within the financial industry that these developments will open up new, improved ways of mitigating risk, including faster and more effective iden-tification of fraud and other illegal, reputationally detrimental and cost-generating activities. And, as the interviewee quoted above continued, “by harnessing big data, we will reduce costs and make our operations more transparent to ourselves and our regulators. We will develop new approaches to mitigate risk, including by faster and more effective identification of fraud and other illegal and costly activities. Using big data and analytics will enable us to provide customers with enhanced information that will allow them to make better decisions.” It was indicated to us that mainly large financial institutions intend to leverage cloud computing across many aspects of their IT infrastructures. According to a representative from a U.S. investment bank, levering the organization’s internal cloud “will have a positive impact on both the unit cost and time to market to provision compute, storage, and connectivity for the increasingly complex businesses of the firm.”Data protection and data security also continue to rank high on the agenda of both banks and regulatory authorities. This is reflected, inter alia, by the following statement from a senior U.K. banking executive: “There is a need to create and carefully follow policies and practices that maintain confidentiality and respect privacy, and there are difficult technical issues related to managing data quality as the volume of data increases and as deployment and analysis move to real time. As a significant financial institution, it will be incumbent upon us to be a leader in thinking through and solving these issues.” Another significant challenge will be to maintain focus. Given the breadth and depth of the data available, and the almost unlimited possibilities to explore and learn from such data, it will be critical to identify and give top priority to those issues which are the most important and of the highest value for banks, regulators, auditors, and customers.In particular, banks with a global business setup identified struc-tural changes in the global economy as the third main cause for the need to change priorities and adapt business models. Along with higher growth rates expected for the developing world, a worldwide change in distribution channels for banking services

is to be expected as a consequence of this development. In the interviews, this opinion was also supported by statements from auditors and regulators.In banking, the internet is now widely used within all customer segments around most of the world to purchase financial service products. Mobile banking is still in early stages of development, but it is following a similar usage curve, with China, India, and the UAE leading the trend in terms of adoption. For the emerg-ing markets, mobile is more than just a new channel but rather provides basic banking facilities to a previously under-banked market. An US-American participant informed us that “the His-panic market have higher penetration of mobile devices relative to PCs, so that the mobile channel becomes critical to reaching and servicing this important and growing part of the population.”According to market analyst specializing on the mobile and web-based banking channels, “mobile banking will continue to be an area of importance and focus for financial institutions.” He based this prediction on the following observations, which indicate consumers’ acceptance of banking behavior on mobile devices:

• Over 25% of mobile phone users access financial service content on their phone.

• Financial services growth on mobile apps has grown 53% year over year

• Paying credit card bills via mobile has grown 30% over the past quarter

• Remote check deposit has increased 40% in past quarter • 2 4% of current banking customers with smartphones

transfer money via mobile

The conclusion drawn from these findings by the analyst cit-ed above is that “banks will need to continue to evolve with changing consumer behaviors as the predicted inflection point of mobile vs. PC banking is expected by end of 2015.”New business models and means of interaction will be required in order to be successful in this changing business context. An-other main trend identified while analyzing the results from our interviews and the electronic survey is that banking institutions and credit card companies will continue to be the most preferred types of companies to offer mobile wallet products. This is based on the finding that mobile adopters are more engaged customers across all products and services (expressed in more transactions, higher balances, higher spending, new accounts, and less attri-tion). There is a strong need for banks to continue promoting innovation in this area, and to continue offering real value and benefits to consumers of existing products and services. So there is a clear consensus among the European and US banks with global business setups that the combination of new tech-nologies and distribution channels, overlaid by trends like de-mographic and global power changes will be the main source for long-term sustainable growth, simultaneously delivering access to new client groups, offering new types of banking services and reducing costs related to traditional value chains. Global banks share the view that leadership management in the future means to be a leader who uses modern technology for both client business and risk management applications.Another area where there is widespread consensus among banks,

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regulators and auditors, in Europe as well as in the United States, and what is also supported by the feedback from our electronic survey, is that new regulatory provisions and improvements to business models require increased spending on technology. The fact that a majority of participants in the online survey only expect moderate increases in IT budget is in a striking contrast to another insight form the interviews carried out. On the part of auditors and banking supervisors, there appears to be a broad consensus that, in the words of one of the interviewees, “IT budgets will have to increase significantly to meet current and future requirements.” According to the same speaker, another complaint frequently voiced by auditors is that “to date, many banks tend to implement work-around and small scale solutions, but this will create significant issues in meeting potential fu-ture requirements.” Such insular, case-by-case solution attempts do not solve the issue that banks are working with historically grown and very fragmented IT and data structures, not capable of fulfilling future performance requirements. For harmonizing the reporting of different ICAAP-relevant risk management processes and consolidation of data provisions for accounting, solvency, treasury and risk management, it is a prerequisite to have a common and consistent database for all reporting re-quirements. Another respondent with an audit background add-ed that “modules and tools must be based on the consolidated database and in the near future, scenarios and simulations on productive data must be implemented and be part of the deci-sion-making process.” Banks today have a complex infrastructure which does not allow flexible implementation of new requirements. To change to a completely new and integrated framework would create huge costs and an operational risk. Furthermore, during implemen-tation the new framework would have to catch up with current changes in the old framework. This will require a large invest-ment but also significantly reduce costs and significantly ease the burden associated with the adaptation to new regulatory requirements.We found considerable differences regarding the way banks will fund this increase in spending. Given the current cost-cutting and deleveraging mode of many banks, the range of answers includes reallocating resources in the overall IT budgets to proj-ects related to risk and regulatory issues, as well as overall ef-ficiency and productivity efforts. However, the overall increase in banks’ spending on technology is ultimately a senior manage-ment decision across the various business lines.The interviews conducted with African banks strongly confirmed the findings from our desk research. Mobile communication technology plays a central role for the development and spread of banking services on the African continent. One of our inter-viewees thus emphasized the high importance of the quality, scope, and reliability of the related infrastructure.Another important finding was that most of the retail banking business in Africa currently involves rather basic services, pre-dominantly related to small payment transactions and (in some cases) micro-loans. In such an environment, it is often difficult for individual banks to differentiate themselves from their compet-itors. Our respondents generally agree that, in such a situation, process innovation is a key driver of competitive advantage,

as it promises to enhance the accessibility of a wider range of products where resources are limited. At the same time, our interviews also provided strong evidence of the need to address data security and privacy issues in a competent and diligent manner to ensure the continuing trust of customers in providers.With regard to the importance of information technology for the purposes of enhancing the customer experience, controlling risks, utilizing market opportunities and optimizing bank-inter-nal processes, the statements of the African interviewees closely resembled those of their European and American counterparts. It was, however, also noted that under the currently prevailing conditions in most of Africa, implementation issues remain a great challenge in this context. Due to the considerable costs associated with establishing and maintaining a powerful and re-liable bank-internal IT infrastructure, the arrival of cloud-based technologies has raised particularly high hopes among many African bank mangers.

6.2 Changing Regulatory and Risk Management Require-ments: Results from In-Depth InterviewsVirtually all participants agree that technology is a key enabler to effectively delivering on the objectives set out in the fields of risk management and regulation.Improvements in data management capabilities and advanced analytics greatly enhance the speed and versatility with which banks can handle the ever-increasing amounts of both struc-tured and unstructured information.U.S. and European banks with a global business setup highlighted the implementation of two parts of the Dodd Frank Act and the respective rules from MIFID II, EMIR, and MIFIR. In this context, a senior manager from a major U.S. pointed to two main issues: He stated that on one hand, “new requirements for the clearing, margining, trading, and reporting associated with derivatives contracts [will drive] more trades … to clearing houses and other trading platforms. Margins may well compress in this process but at the same time new business opportunities will emerge, for example in the area of client collateral management.” On the other hand, he also pointed out that new regulation for retail products will require banks to “adapt to these requirements as they emerge and will modify and/or create products and services to meet consumer needs consistent wih the new rules.”OTC derivatives clearing will decrease the importance of coun-terparty strength in the derivatives business. At the same time, it will allow an improved access to the market by counterparties with weaker credit. The advent of OTC clearing creates a founda-tion for change in the market structure governing the execution of OTC derivative transactions. It will allow markets to become anonymous in some cases and will lead to greater standard-ization. This, in turn, will increase the relevance of electronic trading platforms, and therefore the importance of cutting edge technology for the business as a whole.Interestingly, the increased importance of electronic trading platforms will have a number of side effects that might not be obvious at first sight. As one of the market risk experts inter-viewed stated, “The enhanced role of electronic trading plat-forms will tend to lower the importance of relationships, may lead to a greater fragmentation of order flow, and will probably

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decrease the importance of capital commitment.” Since a higher degree of market fragmentation and anonymity will require par-ticipants to deal with heterogeneous data from several sources with great precision and at high speed, she also concluded that “as a result, technology will become even more of a central core competence and a competitive factor.”A statement from a U.S. banking executive interviewed points in the same direction. He argued that “the most significant im-plications” of regulatory changes “affect the amount and qual-ity of collateral, the prescriptive terms under which collateral is required, and the increase in the number of counterparties involved (e.g. brokers, clearing agents, CCPs) - all of which re-sult in an increasingly complex web of collateral requirements, availability, and movement.” The conclusion he drew from this judgment was equally clear-cut: “As a result, the models and the technology required to support the management and optimiza-tion of collateral will have to undergo significant adjustments. As a consequence, banks are enhancing margin analytics and optimization algorithms to include many additional factors.” Even more specifically, one interviewee from a global market leader in the OTC derivatives markets, explicitly mentioned the leveraging of a linear programming methodology designed to allow clients dynamic, real-time interaction, taking into account several risk factors, collateral availability and allocation.Support for this assessment also comes from our survey results. Combining information gathered from both interviews and sur-vey outcomes, the specific expectations that banks hold in con-nection with big data for progress in risk management activities can be summarized as follows: Big Data and analytics will

• support risk and fraud mitigation, • enhance cyber security measures, as well as• support and refine risk management.

Among the key challenges auditors have identified are:

• financial reporting;• compliance with tightened liquidity standards and the relat-

ed risk management requirements in MaRisk, Basel III, MIFIR, EMIR, and Liikanen;

• deductions for investments in financial sector entities, especially for synthetic and indirect investments;

• multi-curve valuation and hedge accounting; and• subsidiarization and legal entity specific calculations.

Further challenges are likely to gain in importance in future, par-ticularly when it comes to the treatment of trading books, the methods of market risk measurement and management, and the conduct of securitizations. From the viewpoint of regulatory au-thorities and auditors, the existence of a central data warehouse ensuring the constant and easy access to relevant data for au-thorized persons is a key innovation. In this context, harmoniz-ing the reporting procedures pertaining to the different related ICAAP-relevant risk management processes is among the key re-quirements. In this field, there also is a clear view that big data and real-time analytics will help banks in accelerating steering processes, as well as in cutting costs as manual processing steps

become obsolete. At the same time, warnings have been issued not to ignore the substantial risks embedded in these technologies:

• Deficiencies in data quality and the premature interpreta-tion of data can lead to incorrect and misleading analytical results.

• Reliably operating a highly automated process chain requires thorough understanding and close monitoring of the under-lying algorithms.

• Operational risks can be considerable.• The more a bank relies on a system, the more it is dependent

on its provider.

6.3 Technology and Process Innovation: Results from In-Depth InterviewsThe intention of banks in leveraging their use of technology is to achieve process innovations directed at the attainment of specific, targeted performance improvement goals. In the fol-lowing, we reproduce four key statements from our interviewees on how technology can enhance value creation within banks:

• According to a senior operations manager from a leading UK bank, “the elimination of low-value processes reduces ex-penses, frees up critical resources, and thus fosters a stronger focus on contributing to customer satisfaction.”

• An expert on customer relationship management in banking told us that “the re-engineering of processes and enhance-ment of tools in order to improve response time will give the customer more expedient service and allow a more rapid re-action to market developments, resulting in lower customer attrition and increased revenue. New technologies, integrat-ed with a bank’s business processes, are enabling improve-ments in their ability to better understand and react to their customers’ needs. This will help to improve client-servicing platforms and allow more flexibility, thus accommodating the increasing want of customers to use their own devices.”

• According to a “Improved streamlining and standardization of process steps will minimize the possibility of errors or exceptions, reduce the need for corrective action to resolve issues, and ul-timately minimize the hazard of process failures that can entail unwanted supervisory measures or customer complaints.”

“Strengthening the performance of processes will allow for max-imum leverage of the workforce and contribute to increasing job satisfaction and employee retention.” Moreover, banks have expressed several expectations regarding big data for progress in process innovation. Here, the most important points are:

- the facilitation of product customization and targeting, - the improvement of trading strategies, - an amplification of the ability to gather and harness large

amounts of information, allowing a more efficient conduct of the business, as well as an improved understanding of and responsiveness to market dynamics and customer needs,

- a more comprehensive understanding and analysis of com-plex internal and external issues, facilitated by a more im-mediate access to all relevant details,

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- a higher quality and speed of decision-making processes, and - a faster, more accurate identification of possibilities for revenue

enhancement and cost reduction for banks and their clients.

We want to differentiate between the different findings of the study based on spate headers, such as customer relationship, risk, and regulatory changes.

6.4 Results of the Online Survey For a better evaluation of the results of the study, it is important to consider the average, the maximum and the minimum num-ber of selections per answer across all questions (Figure 11). These numbers indicate a rather positive voting or a generally high approval across the survey with only 10,50% on average negative but 63,55% positive answers. It´s very pleasing to see that only 2,56% selected N/A on average, which indicates that most of the participants stated their opinion.The first question asks for the importance of information tech-nology in the institution’s strategy and can be seen as a lead into the following deeper questions. 83% of all participants valued it with a 4 or 5, which means important to very important. Only 3,5% see it as irrelevant (Figure 12).The participants were very consistent in valuing the benefits of process innovation and IT. The biggest agreement with 83% pos-itive votes is the help to “meet regulators’ requests”, followed by “enhance customer satisfaction” (77%) and “reduce costs” (71%) (Figure 13). The latter does not necessarily mean to increase rev-enues, as 10% were critical of that and a further 23% marked it with a neutral indicator. Nevertheless, the positive effects of IT cannot be denied.An important topic from the regulatory side, as a result of the crisis, is availability and storage of data. It has been shown that even for large and sophisticated banks it was hard to get the requested information regarding risk or liquidity within a reason-able amount of time. Question 3 asked about the importance of the management of big and real-time data for banking. Both are considered fairly equally with 45% (big data) and 47% (real-time data) answering “very important” which increases to 88% and 79% respectively by including the vote “important” Figure 14). None of the participants find it very unimportant which is quite a rare outcome within this survey.So the majority of the participants saw the importance of man-aging big and real-time data but how did they think their current systems and processes were capable at analyzing and simulating various key factors in real time? The factors were given as value at risk (VaR) and expected shortfall, LCR and NSFR, Economic capital, Regulatory capital and Leverage ratio. All in all the result shows a more sceptical picture than for previous questions. VaR and expected shortfall are seen, with close to 60%, as capable, whereas only 34% is of the same opinion regarding LCR and NSFR. Leverage ratio is considered critical as well with only 45% positive and 18% negative votes. This question also received the highest portion of “N/A” responses throughout the survey which shows a high degree of uncertainty (Figure 15).Question 5 reflects the importance of management needs re-garding specific systems or processes. Specifically it asks about “Real-time analytics”, “On-demand drill-down functionality”, “Ag-

gregation and comprehensiveness” and finally “Simulation and stress testing”. “Aggregation and comprehensiveness” is seen as most important, with 84% clasifying it as a 4 or 5. “Real-time analytics” are seen as important (4 and 5) by 63% but also as unimportant (1 and 2) by 15%, which is quite high compared with the overall rather positive opinions in this survey. The other two are seen as important and very important by 75% of the partici-pants, in which “Simulation and stress testing” receives also 7,4% negative opinions (Figure 16).Another lesson learnt from the crisis is the difficulty to get re-al-time, aggregated data from decentralized or locally indepen-dent units in different countries and time zones. Surprisingly the result of the survey shows that no one is unhappy, as 0% answered 1 (Not at all), and 81% ranked it a 4 or 5,showing a general sat-isfaction and trust for the internal systems (Figure 17). As this survey aims to capture the general opinion of the employees across different departments and different levels of seniority, the general opinion may actually be that these processes and technologies do exist.Looking more into the future, potential solutions or improve-ments for aggregating or real-time data could be cloud comput-ing or in-memory technology. A further development, already highly used in Africa, is mobile computing which leads to the next question and the expectations of participants for these new technologies. This question received a very different spectrum of answers. Cloud computing got the maximum negative values across the whole survey, with 9,57% for rank 1 and 19,13% for rank 2. Sur-prisingly, even in-memory technology and Mobile computing were for both ranks 1 and 2 far above average. Furthermore, the number of responses for the top ranks 4 and 5 wasbelow average in each if the four components . The biggest chance is seen for Mobile computing - for 65% of all participants (Figure 18).Question 8 focuses on the solutions coming from professional providers concerning risk management, liquidity management, and regulatory requirement. Most of the participants indecisive with regard to this question. The highest number of negative and lowest number of positive votes were found in this question. Together with the very high number of “N/A” votes, it shows the dissatifaction with the solutions provided (Figure 19).Going back to mobile banking which is definitely on the rise, question 9 asked about the importance of mobile banking in the next decade. This question received the highest counts through-out the survey for rank 5 with 55.22%. Mobile computing as an innovation for institutions was seen more critically in question 7. This result was one of the clearest and strongest (Figure 20). To address all the changes and needs one should expect IT budgets to increase. On the other hand, IT departments are non-profit centers and therefore typically viewed very critically; IT departments have to save money on each cost-cutting round. Nevertheless, 61% of the participants expect an increase in the IT budget of at least 25% (Figure 21). ConclusionInformation technology in general is considered very import-ant by the participants for future strategies. It was considered most important, followed closely by another important future

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Figure 13: Process innovation

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Meet regulators request

Increase revenues

Enhance customer satisfaction

Reduce costs

5

4

3

2

1

NA

77 87 1446

78

59

95

100

93

96

40

54

30

9

20

6

4

2

3

21

1

1

2

Figure 12: Importance of information technology

0% 10% 20% 30% 40% 50% 60%

1

2

3

4

5

NA How important is information technology in your institution’s strategy?

Can process innovation and IT help to meet regulators’ requests, increase revenues, enhance customer satisfaction and reduce costs?

# Average Top Low1 2,61% 9,57% 0,00%

2 7,90% 19,13% 1,74%

3 23,39% 43,48% 8,26%

4 37,06% 50,43% 22,61%

5 26,49% 55,22% 5,22%

NA 2,56% 6,96% 0,43% Figure 11: Weighting Range

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development, mobile banking which is already strong in certain countries outside the EU. Also a key topic for companies is the management of real-time and big data. However, there are quite enormous gaps in the services of solution providers for important upcoming issues and therefore the necessity of increasing IT budget is predicted.

6.5 Breakdown of Results for Key MarketsThe two key markets Europe and U.S. we have covered in this research study are very similar regarding their strategic views on main challenges. But at the same time they are in a completely different initial position for establishing their future roles in the global post crisis financial industry.

We found a clear consensus that the main competitive factors are given by:

• Equity• Liquidity• Strong distribution and communication channels in emerg-

ing markets • Innovative and competitive services in growth markets• Powerful risk and liquidity management infrastructure

There is also widespread agreement that in future, banks’ busi-ness models will require a significant increase of technological capabilities regarding risk and liquidity management as well as distribution channels and platforms for banking services. On the other hand, higher demands for technology and the stronger requirements on quality and quantity of risk capital make the business model of banks more expensive. There is a strategic need for economies of scale and a growth story in order to keep a business model profitable in spite of rising expenses. But there is no sustainable growth strategy in many segments of the tra-ditional banking business. In particular, the European market is overbanked. On the other hand, the fast-growing retail markets in the emerging countries are characterized by new distribution channels and service platforms.Globally acting banks have similar views on future challenges with regard to the dominant role of technology & infrastructure for risk management, as well as for the realisation of business opportunities. There is agrees that transformation of banks to-wards a profitable and competitive future business model re-quires the strengthening of resources like capital, liquidity and technological infrastructure. Banks have realized that excel-lence in risk management increasingly becomes a competitive factor not only for regulatory reasons but also for the detection and realization of business opportunities based on an adequate and competitive pricing framework for relevant risk factors. Banks being successful in resolving the consequences of the financial crisis will be superior to others for two main reasons:

• Financial resources accumulated can be used for building new distribution channels for banking services

• The establishment of a strong technological platform in combination with greater risk-bearing capacity can be used to achieve and maintain a role as a leading market maker in

newly regulated global derivatives markets as well as in the global equity, bond and commodity markets

But a necessary condition for success is to have a well-filled “war chest” available for financing the required technological setup. Europe and the German market is characterized by overbanking and, on average, rather weak returns. The U.S. banking industry, in contrast, is dominated by a few large, global banks sharing a huge and profitable home market. Moreover, the large U.S. banks have succeeded in re-building a profitable business model. As a consequence, it is evident that the U.S. banks use the resources available to them efficiently to increase their technological and financial dominance. This enhances their capacities to gain market share both in the global equity, bond, and derivatives markets, as well as in the fast-growing retail markets in the emerging economies. This leads to the expectation of a strengthened U.S. dominance in the global capital markets in the post-crisis phase, with the main competitors coming from Asia.In Europe we have an opposite picture. Due to trends like the Eu-ropean corporate funding disintermediation, traditional business areas such as lending business are extremely competitive and provide only weak margins. As a consequence, European banks do not have resources comparable to those of their U.S. compet-itors. Even more importantly, in many cases the balance sheet restructuring processes that became necessary because of the recent crisis have not been finished yet.Also, the size of the banking sector compared to the size of the economy is less favourable in Europe than in the U.S. The public and political pressure on banks is significant. Concerns regarding the future role of Europe in an important global key industry are under-represented in the public debate. Thus, the major European banks suffer a big disadvantage compared with U.S. competitors in the global competitive environment. This leads to a redistribu-tion of market shares: It is anything but unlikely that the financial industry of the future will be dominated by U.S. banks and their Asian competitors, and that Europe becomes a quantité néglige-able in a key industry. Banks that offer little profitability due to the lack of a sustainable business model are also a threat for the stability of the financial system. The cost associated with the risk capital, the advanced technology and the professional staff required to create a sus-tainable competitive advantage requires economies of scale. This calls for a consolidation of the European banking industry at a European level. Government policies in Europe need to find an answer to these challenges and to the question how the Euro-pean banking industry can become competitive in a globalised environment.

6.6 Results from a Regulators’ PerspectiveThere is a widespread agreement among regulators and supervi-sors regarding the increased role of risk management for strategic business planning, capital management and capital planning, as well as for advanced and integrated risk modeling and integrated liquidity management. A senior executive from a regulatory au-thority summarized this by stating: “Risk management needs to be closely involved in strategic decisions to clarify the risk return

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Figure 15: Capability of current systems and processes

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

LCR and NSFR

Economic capital

Regulatory capital

Leverage ratio

VaR and expected shortfall

5

4

3

2

1

NA

49 88 1356 1212

79 1174 142824

82 1160 162041

93 1063 112231

52 1595 132827

To what extent are current systems and processes you have in place capable to analyze andsimulatepotentialeffectsofbusinessdecisionsonvariouskeyfiguresinrealtime?

Figure 16: Senior management decisions

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Real-time analytics

On-demand drill-down functionality

Aggregation and comprehensiveness

Simulation and stress testing 5

4

3

2

1

NA

77 96 1238 25

79 114 427 6

63 110 944 22

64 79 51 1123 2

How important are the following aspects of systems and processes in order to support senior management in its decisions?

Figure 14: Importance of data

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Management of big data

Management of real time data 5

4

3

2

1

NA

108 74 441 3

104 99 521

Of which importance will the management of big data and real-time data be for banking?

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5

4

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NA

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Risk management

Liquidity management

Regulatory requirements 22 59 99 13532

12 64 100 13635

15 64 100 13533

How big are the gaps in solutions from professional providers concerning risk management, liquidity management and regulatory requirements?

Figure 19: Gaps of service providers

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

In-memory technology

Cloud computing

Mobile computing 76 10 25

4

3

2

1

NA

73 2940

57 22 250 4455

78 7 332 2981

How important do you expect the following innovative, new information technologies to be for your institution in the future?

Figure 18: New information technology

0.00% 20.00% 40.00% 60.00% 80.00% 100.00%

Meet regulators' requests

Increase revenues

Enhance customer satisfaction

Reduce costs

To which extent are processes and technologies that you have in place capable of aggregating relevant risk factors from different subunits on a group level in real time?

Figure 17: Aggregation of data

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0% 10% 20% 30% 40% 50% 60%

1

2

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4

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NA

How important will mobile banking be in banking in the next decade?

Figure 20: Mobile banking

0% 10% 20% 30% 40% 50% 60%

Decrease by more than 25%

Decrease up to 25%

Stable

Increase up to 25%

Increase by more than 25%

NA How do you expect your institution’s budget for information technology to develop over the next three years?

Figure 21: IT budget

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profiles of products and business segments.” Regulators, super-visory authorities agree about the significant increased role of innovative IT in the post crisis infrastructure of banks. A repre-sentative quote from a related expert reads: “All businesses re-quire fast, reliable, effective, efficient, no-failure, front-to-back system solutions and extensive, timely data analytics as well as extensive risk management calculations.” We received many proposals from our interviewees about important innovations like “central data warehouses to simplify data availability” and “sophisticated analytics to help detect and hopefully protect against fraud”.In line with the clear view about the increased strategic role of risk management we observed a consensus among regulators and auditors that in many banks, the existing IT infrastructure is far away from what would be necessary from a regulatory view-point. As the representative from a global audit firm put it, “we estimated that a great percentage of the currently implemented processes with most of the banks is insufficient to meet future requirements.” Another representative from the audit business added: “Consolidation of data provisioning for accounting, sol-vency, treasury and risk management data is prerequisite to have a common and consistent data base for all reporting re-quirements. Banks today have a complex infrastructure which does not allow flexible implementation of new requirements.”At the same time, representatives of regulators, supervisory bodies and auditors call for changes in the IT infrastructure of banks – even the process of change is difficult and even cre-ates operational risk. This perception can be supported by the following quote from one of our interviewees: “The existing IT infrastructure is historically grown, very complex and quickly changing, especially in the big system relevant banks, such that a change to completely new and integrated framework would create huge costs and an operational risk. Further, during im-plementation the new framework would have to catch up with current changes in the old framework. Besides that huge invest-ment, it would significantly reduce costs and prevent future cost when adapting to new regulatory requirements.”Automation is the key word for regulators and auditors and one of thesis main requests for banks, as is evidenced by the following quotes from our expert interviews:

• “Systems need to be both, fast and flexible with automated ad hoc stress testing capabilities”

• “Automated and flexible data analytics and risk calculations across all risk drivers, products, segments, legal entities”

• “Flexible and customized modules for automatic analysis and stress scenarios”

The question thus arises which features will characterize an IT infrastructure in a bank as state-of-the-art from a regulators perspective. The answer we received from a senior executive from a regulators authority is quite simple: “Timely data avail-ability is the key.” A colleague from another regulatory authority expressed it more precisely: “Automated ad hoc stress testing functionalities, correct, complete, granular product data, timely balance sheet data, timely and complete counterparty data for the entire bank or group.”

But does “timely” mean “real-time” in this context? Or, if not, what are the sensitive parts of a system relevant banking or-ganization where identification, assessment, and management of the inherent risk in real time are a big advantage, or even a must be achieved in spite of the considerable additional cost involved? A representative answer from one of our interviewees reads: “Liquidity management, and front office trading depart-ments managing credit risks and market risks”. However, we also found out that there is a difference in the use of the word “real-time”, depending on whether this term is used by an IT professional perspective or an expert on regulatory issues. From a regulatory perspective, “real-time” is often used as a synonym for “within no more than one day”. Another important key word for regulators and auditors is har-monization of data sources and processes, especially as one senior executive of a supervisory body expressed it, the “har-monization of the reporting of the different ICAAP-relevant risk management processes”.Regulators and auditors have a clear view about the import-ant key role of IT in banks and they have common perception that there is a very strong need for improvement in this field, which comes hand in hand with their requests for increasing IT budgets. Regarding innovative key word like Big Data, Cloud Computing, Real-Time Analytics, etc., regulators and auditors tend to have a very pragmatic, “down-to earth” viewpoint. Their perspective is more strongly influenced by specific purposes, like process and data harmonization, timely availability of analytics, risk figures, along with regulatory ratios, balance sheet data, and stress test results. While banks are more strongly driven by technological innovations and related business opportunities, regulators want banks enforce to fulfill regulatory tasks and risk management targets. But as soon as it becomes obvious that new technologies will be the most efficient key to close exist-ing gaps between existing capabilities and requirements, these innovations become also a “must” from regulator’s perspective.

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7 BEST PRACTICE BANK

7.1 Creating Unique Value Together with Customers 7.1.1 Addressing Three Strategic Challenges from the Current Market Environment We want to discuss here the fundamentals of best practice principle 10 from chapter 3.2 of our research study. The key to rebuilding trust and bettering relationships with customers lies in improving cooperation. By facilitating com-munication with customers, banks gain the capacity to improve their product and service portfolio where customers value it most. In this context, it is important to recognize that both businesses and private citizens have increasingly opened up to the opportunities created by innovations in information tech-nology: They use mobile, interactive digital devices and social networks to make up their minds about which companies they deem reliable and what products they purchase, and they of-ten even use social media to let others know how they were attended to. In response, many banks have been investing in applications for tablet computers and mobile phones with internet connectivity that enables customers to conduct a large variety of banking transactions while on the go. At least some of them also use the capabilities of social networks to attract “fans” to full-fea-tured social network pages, seeking to strengthen the image of their brands and have consumers share personal information. However, the use of technology alone will not automatically be a source of competitive advantage. Rather, what matters is the way banks use it to enhance customer satisfaction. Creating added value requires a lot more than pinning technologically sophisticated applications onto a traditional business model. More specifically, we can single out three strategic necessities:

(1) Synchronize traditional and new banking channels. The number of channels and different platforms for the deliv-ery of banking products and services has grown rapidly and will probably continue to do so. This increases the degree of complexity in processes. Banks will need to gear their back-end systems to provide a consistent experience to custom-ers independently of the particular channel they use. Prac-tice leaders in this field virtually never have to request the same piece of information from a customer more than once. By gathering data imparted by customers at each point of contact in a highly developed customer relationship man-agement system covering all channels, they ensure that the relevant information can be retrieved whenever the cus-tomer comes into contact with the bank. This enables the bank to recognize the customer’s demands in a rapid and reliable manner and fosters a more personalized customer experience.

(2) Re-design bank branches. In the past, many banks have used information technology primarily as a means of reduc-ing costs. Encouraging customers to carry out transactions through websites, mobile applications, and self-service ter-minals, they have closed a considerable number of full-ser-vice branches. Yet while the potential cost savings resulting from the adoption of a self-service model may look attrac-tive, the likely long-term losses that would result from leav-ing customers entirely to their smartphones and tablets are too large to be acceptable. Although a large and growing share of the routine transactions have moved on-line, bank branches continue be the main places where can find ex-pert assistance in more intricate financial matters, e.g. business financing, real estate funding, investment strategy design or retirement planning. Moreover, even customers who already conduct the bulk of their financial transac-tions on-line often feel more at ease if they can physical-ly interact with the people who look after their money. Seeking to improve the amenities for visitors to their full-service branches and, at the same time, achieve effi-ciency gains, some banks have hence reorganized their branch networks: On one hand, they set up a limited num-ber of flagship full-service banking hubs in attractive loca-tions, some of which are laid out more like shops or cafés than “traditional” bank subsidiaries and designed to cap-ture customer attention and curiosity. On the other, they establish several smaller, peripheral branches to assist customers with routine transactions and market less com-plex products like, e.g., consumer loans. In cases where the geographical distance tends to inhibit customers’ access to expert financial advice, combining videoconferencing facil-ities with on-line appointment scheduling tools may also offer great benefits.

(3) The use technology to facilitate organizational learning. Gathering more and more information on financial mar-kets, products, and services from the web, many customers have become increasingly well-informed and self-assured. From banks, they demand high-quality personalized ad-vice for the key financial decisions they face during their lives. Succeeding in this market environment requires the build-up of superior advisory capabilities. This places high demands on the persons involved, not only in terms of mar-ket and product knowledge, but also with regard to per-sonal communications skills and media literacy. In order to make the best possible use of the potential higher-skilled (and, usually, better-compensated) employees offer, banks have to employ technology to ensure the availability of their knowledge and experience as widely as possible

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Best practice Bank | Banking Study

within their networks, and across a large variety of media. The ability of an organization to adapt to changes in its market environment is among the key factors for success in business. Due to their highly interactive nature, web-en-abled social media have developed into both a catalyst and a provider of indicators for economic and societal change. To banks striving for a genuinely customer-centric way of doing business, today’s internet hence is a lot more than just a global medium offering superior possibilities for the cre-ation, precise targeting, and delivery of innovative advertis-ing campaigns. As today’s “Web 2.0-savvy” consumers gath-er and exchange information, and formulate opinions about financial products and services on-line, it is only natural for them to want providers to listen, respond to, and serve them through social media channels too. Just as much as they expect banks to share offers and information on upcoming events, they call for opportunities to give feedback. Banks with competence in these areas can make effective use of social media channels to allow a high degree of personal-ized communication with customers at a reasonable cost. More importantly still, banks can improve the processes of collecting, pre-processing and analyzing customer in-formation by combining internal data with those released on the web to obtain further insights into behavioral pat-terns, sentiments, and wants of customers. This is, how-ever, by far easier said than done. Under the conditions that prevail today, data do not only become available in enormous quantities, but also come from a large number of platforms, in several different formats, arrive at unprec-edented speed and may, in some cases, lose their validity rather quickly. Despite their considerable capacity, versa-tility, and power, traditional relational database systems and statistical software packages are often incapable of dealing with such quantities of heterogeneous data in an acceptable time frame. In response to this challenge, sci-entists and engineers have made considerable progress in developing new types of software which can simulta-neously utilize a large number of processors, or work on several servers, thus dramatically reducing response times and making the execution of several database queries pos-sible at the same time. Together with the significant ad-vancements that have taken place in the field of statistical classification and pattern recognition, this has given rise to a variety of innovative techniques for uncovering hid-den patterns, exploring previously unidentified linkages, predicting likely future developments and visually repre-senting key results in an interactive, intuitively accessible manner. These techniques, which are often summed up under the term “big data analytics”, can lead to high busi-ness rewards: for instance, they can help determine how different groups of depositors will react to a change in short-term rates, sort out which persons will be particularly interested in new product offers, and greatly improve the reliability of credit scoring and collateral valuation process-es. Moreover, by detecting and quantifying complex depen-dency structures involving several economically relevant variables, such analytical instruments have proved to be

extremely helpful in detecting cross selling opportunities. Thoughtful application of these innovative techniques has substantially helped some banks gain and sustain an edge over their rivals. Yet it also deserves to be mentioned that banks must be aware of, and carefully manage, the risks associated with applying the related technologies. In order to ensure the protection of data under its control from un-authorized access, improper use or disclosure, unauthorized modification, accidental loss or undue destruction, banks will have to develop and effectively implement adequate governance models which not only have to comply with existing regulations but should also aim at averting rep-utational damage. Given the high speed of technological advancement, ever changing legislation and jurisprudence, and the possibility of shifts in public attitudes towards these issues, this is not a one-time task but a constantly moving target.

7.1.2 Summary of Key Statements from Questionnaires In the answers received from the questionnaires, there was a consensus that a key imperative for IT is the alignment of the opportunities provided by new distribution channels with busi-ness priorities, in order to improve customer experience, as well as productivity as well as efficiency. The requirements of data integrity and risk reduction, and the imperative of taking into account all relevant interrelations with operations, legal, tax, HR and other fields have highest priority for successful implemen-tation of new business technologies. One of the key statements from the perspective of regulatory authorities and auditors was the prediction that banking will necessarily become increasingly intertwined with customers’ digital lives. The rationale for this expectation is the great importance that the growth of mobile has for banks. The equipment of mobile phones with greater and qualitatively improved functionalities is bound to transform the traditional interaction model with the consumer.

Well-equipped bank branches and flashy websites will no longer be sufficient to meet the demands of customers who expect services on the move

Another frequent and very interesting statement was that that in most cases, closely cooperating with innovators from IT, telecommunications, and non-traditional banking providers will prove more effective, offering greater chances for success than working on one’s own. Identifying partners to acquire or help deliver the vision hence becomes of critical importance. This reflects the observation that well-equipped bank branch-es and flashy websites will no longer be sufficient to meet the

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demands of customers who expect services on the move. Loca-tion-based offers, timely and relevant content and interactive applications will form the basis of the mobile customer’s en-gagement with their banks.

7.2 Securing Compliance with Risk Management and Reg-ulatory RequirementsHere we would like to discuss the fundamentals of best prac-tice principles 5- 9 from chapter 4.2 of our research study.

7.2.1 New Regulatory Standards Following the Recent Crisis The new regulatory framework for banks and banking systems referred to as Basel III is often regarded as the most momen-tous driver of change in the banking world today. Key features of this new international regulatory framework include

• an enhancement of banks’ capital base through increased capital requirements, more rigorous capital standards, and the mandatory build-up of capital buffers,

• more stringent standards for counterparty credit exposures arising from banks’ derivatives, repo and securities financ-ing transactions,

• new provisions for liquidity management and monitoring, and

• a strict limitation on the build-up of leverage as a safe-guard against the under-estimation of risks due to inade-quate models or model inputs

The new regulatory frame-work for banks and banking systems referred to as Basel III is often regarded as the most momentous driver of change in the banking world today.

Owing to the new global liquidity standards, banks, for which maturity transformation continues to be a main source of in-come, will have to strengthen their efforts to attract and retain customer deposits, issue more long-term floating rate debt, and hold a larger share of their respective asset base in the form of instruments that are stable in value and can be easily turned into cash at short notice. Credit securitization will remain an import-ant source of funding (and capital relief) for many institutions, yet the new rules applying to this field and greater risk aware-ness on the side of investors will strengthen the transparency requirements for such products and require originators to retain a larger stake in related transactions than previously usual. Moreover, compliance with the Basel III rules will necessi-tate an increased degree of alignment between the risk and

finance functions and an integration of their respective data pools within the bank, enabling a clear focus on risk-adjusted value-added metrics. In this context, the perceived failure of many previously established risk models – and the data fed into them – to produce reliable, early warning indicators of im-pending market dislocations necessitates a major overhaul of existing modeling and data management practices. Particularly in over-the-counter (OTC) derivatives trading, the joint occurrence of time-varying counterparty credit quality and exposure, and the presence of “wrong way risk”, i.e. the possibility of a negative correlation between both, currently command a high level of attention. The calculation of a cor-responding indicator, the Credit Value Adjustment (CVA) has become part of the mandatory regulatory capital calculation under Basel III. For banks with considerable OTC derivatives exposure, effectively controlling this often highly volatile quantity and hedging against unwanted risks in this field is a formidable task: it usually involves the need to aggregate in-formation from a variety of asset class specific trading systems used with different sub-portfolios on a daily basis in real time and hence, constitutes a major operational and technological challenge. As banks with high volume trading desks tackle this challenge, computational procedures capable of allocating computational demands to several processors will be of great benefit: by allowing a faster processing of batch jobs, they will be able to supply decision makers with ex ante information on possible transactions, and help them assess the likely impli-cations for capital requirements. The attainment of this goal, however, necessitates the consistent coupling of data from the bank’s risk management and trading operations. In more general terms, the tasks of adequately assessing the probability and severity of rare, high-impact “tail” events and realistically aggregating risk contributions from different sources allowing for nonlinearities in their dependency struc-ture continue to be at the center of interest for practice leaders in banking and supervisory authorities alike. The failure of the traditional Value-at-Risk to capture events beyond the confi-dence level threshold have prompted calls for a supplemen-tation or even replacement of this metric by Expected Short-fall, i.e. the statistically expected loss amount occurring if this threshold is actually exceeded. Extreme value theory, a branch of statistics focusing on very large deviations from the mid-point of frequency distributions, has made important contribu-tions to the estimation of this measure in practice. Given the large amount of time and resources leading banks invest in the building and calibration of risk models, it must not be forgotten that the ongoing validation of these models on the grounds of observed data is an equally important task. Model validation essentially consists of the ex-post compari-son of ex ante predictions and observed values of the variables of interest, and involves statistical appraisals of whether the deviations between the two are small enough to be considered as random or so large that they call for a re-parameterization or reformulation of the model. Performing this assessment is often anything but trivial since it may involve a large number of resampling rounds in order to produce valid uncertainty margins for the model output.

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The task of adequately performing the tasks of model selection, calibration, and valuation places high demands on the compre-hensiveness, validity, and consistency of the related data. One of the key conditions for attaining such a high degree of data quality is that the processes of data generation or collection, the information flows, and the various selection, combination and transformation processes that data undergo while being utilized within the organization, are documented in a comprehensive, precise, and intelligible manner. Given the high demands for flex-ibility made on the related systems and processes, traditional ap-proaches to documentation based, for example, on spreadsheets or presentations, often run the danger of falling out-of-date all too quickly. Here, recent progress in the field of meta-data tools designed to standardize and facilitate synopses of basic informa-tion about data, can greatly facilitate the processes of locating, understanding, and working with particular instances of data. As far as technology is concerned, analytical solutions for risk management problems have traditionally been based on rela-tional databases for storing information, and on compute grids for the calculations. This clearly is appropriate if the desired functionality related systems are confined to nightly batch runs. Given the recent growth in demand for real-time analytics, how-ever, the considerable disk and network resources required by databases have increasingly turned them into limiting factors. An effective solution to this problem is offered by multi-tier architectures: They store intraday data in an in-memory cache, thus reducing response delays to human-unnoticeable amounts, while historical data is held in databases, which allow for com-prehensive data mining and reporting operations. Meanwhile, processors with multiple independent CPUs and advances in 64-bit computing have made it possible to store terabytes of data completely in RAM, thus markedly reducing the necessi-ty of reverting to electromechanical storage products, e.g. hard disks. As a consequence, In-Memory Data Grid, a data structure located completely in RAM and distributed across several serv-ers, has become the state-of-the art storage technology for in-traday data. Due to the high standards which the data basis of bank-internal risk models has to fulfill in order to obtain supervisory approval, another key area of concern for decision makers is the ability of IT systems to handle a seemingly ever-increasing amount of information without sacrificing performance or causing perma-nent, significant cost hikes. One concept that holds out consider-able prospects in this context is cloud computing, i.e. the on-de-mand provision of IT infrastructure, e.g. data storage, computing power or software, via a real-time communication network like the internet. Its application releases users from the necessity to operate the corresponding facilities locally and on their own, enabling them to pick and choose services from one or more (often geographically remote) providers as needed. On the side of the user, the enhanced flexibility of this model supports a faster development of new products and enables a swifter re-sponse to new demands from outside the organization, sparing the need for huge ex-ante investments. With the responsibil-ity for operating the technology resting with the provider, us-ing cloud services can enable banks to achieve a high extent of data protection and fault tolerance, as well as improved

back-up and disaster recovery facilities at a reasonable cost. Yet it should be kept in mind that fully realizing these poten-tial benefits requires a high degree of reliability on the side of the provider. Organizations seeking to move some of their IT operations to the cloud are strongly recommended not to base their provider selection on perceived cost savings alone, but to look for a partner with clear evidence of comprehensive exper-tise in the management of enterprise data processing centers. Suppliers must give highest priority to data security (e.g. by encrypting all stored and transmitted data) and data integrity, have a proven ability to withstand denial-of-service, virus, and malware attacks from outside, and boast a record of very high

Using cloud services can enable banks to achieve a high extent of data protection and fault tolerance, as well as improved back-up and disaster recovery facilities at a reasonable cost

availability (e.g. > 99.9% during working days) as well as a wa-tertight disaster recovery plan. A clear process of identifying problems and developing resolutions must be in place, and the service level agreement between client and provider must cover all important details about availability, customer sup-port, response times, and performance benchmarks. From a regulatory point of view, cloud computing is a form of outsourcing. As a consequence, the same supervisory require-ments that apply to “traditional” forms of outsourcing also apply here. From this, it follows that banks using cloud com-puting services are obliged to carry out a comprehensive due diligence of all related elements. This involves carrying out an identification and assessment of the nature, scope, complexity, and risk content of all activities and processes entrusted to external providers. Since the legal responsibility for the time-ly, complete, and accurate fulfillment of all risk measurement and reporting duties prescribed under the Basel rules remains with the bank, applying cloud computing for these purposes requires banks to monitor the related processes as closely and regularly as they would those internally.

7.2.2 Fraud Detection, Analysis, and Prevention According to a recent estimate by the Association of Fraud Examiners, the total of losses incurred by public and private sector organizations worldwide due to fraud amounted to a shocking USD 3.5 trillion in 2011. Therefore, it is obvious that identifying fraudulent transactions, limiting their impact and preventing their re-occurrence can contribute greatly to the value an organization creates. The challenges banks face

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when working towards this goal include the following needs (see Principle 9)

• to identify fraudulent behavior before (significant) losses occur,

• to keep step with rapidly changing behavioral patterns in this field,

• to reduce the frequency of “false alarms”, • to speed up and improve the efficiency of fraud detection

and prevention activities through automation, and• to keep any unwanted impact that fraud-related activities

have on the core business as small as possible.

For the detection and analysis of fraudulent transactions, re-cent advances in statistical pattern recognition models, com-bined with advanced text and image processing methods, have proven to be very rewarding. Clustering procedures, for exam-ple, can be used to group large numbers of mutually similar transactions together, so that the sudden occurrence of materi-al behavioral deviations from previously observed patterns can trigger the activation of a warning signal. Probability density estimates of the timing and size of individual transactions con-stitute another useful instrument for the discovery of atypical transaction sizes and frequencies which can be indicative of the unlawful appropriation of credit card or account data. For the detection of financial statement fraud, e.g. the overstate-ment of asset values or sales, or the concealment of losses or liabilities, the use of artificial neural networks and nonpara-metric regression techniques have been able to improve signifi-cantly over traditional auditing techniques. Fruitful as they are, all of these methods have in common that they are extremely data and computer intensive. In order to deliver the full potential, the input data they require must be rapidly accessible regardless of where they come from with-in the organization, and calibration of the models separating unsuspicious and suspicious observations must be feasible within strict time constraints, thus ensuring rapid adaptation to changing behavioral patterns. Ideally, the considerable complexity and data-intensity of these procedures will be not felt by business users, whose task it is to investigate and evaluate alerts, to take action on substantiated suspect cases, as well as to enforce, manage and improve fraud prevention controls and policies. This calls for an intuitively accessible user interface for ana-lysts, investigators, and senior decision makers.

7.2.3 Anti-Money Laundering The term “money laundering” denotes the act of concealing the unlawful sources of money gained through illegitimate activities in order to give the impression that it came from a legitimate origin. Since banks are often misused as mon-ey-laundering channels, supervisory authorities demand that banks have and apply reliable, high-performing processes, systems, and procedures for the detection and prevention of such transactions. Failure to discover and effectively combat unlawful transactions may give rise to heavy sanctions in both monetary and operational terms and even go as far as to

endanger the survival of the institution. The most important instrument in the combat against money laundering is the non-admission of anonymous financial trans-actions. This is reflected in the “Know Your Customer” principle: banks are obliged to check a customer’s identity and examine financial flows for anomalies that may point to illegal actions. Examples of such suspicious procedures include (but are by no means limited to): Any attempts to preserve anonymity or avoid personal contact with the bank,

• The frequent presentation of new identity documents or the presentation of identity documents of doubtful authenticity,

• The use of third parties as figureheads,• The withdrawal of requests when further investigations

have been initiated,• Multiple, consecutive changes in the information provided

on identities, addresses, telephone numbers, beneficiaries, banking connections, or payment modalities,

• The use of “letterbox firms” as shell companies, • Known criminal proceedings,• The division of large transfers of money into smaller, “un-

suspicious” parts, possibly involving several different banks or accounts,

• Transactions that appear economically nonsensical, e.g. the repayment of loans or termination of bank accounts in un-usually short periods of time, or

• Payments being made from abroad without any plausible reason, particularly if the nations involved are on the list of non-cooperative countries of the Financial Action Task Force on Money Laundering (FATF)

It should be obvious from this non-exhaustive enumeration, that given the enormous amount of payment related infor-mation banks are processing every day, the mere rule-based examination of transactions alone might easily fail to detect some of the more complicated transaction patterns used by money launderers today, such as round-tripping or deliberate under- or over-invoicing. Here, too, analytical techniques like clustering, frequent sequence mining, or supervised learning algorithms are of great use in uncovering accumulations of anomalous actions or financial flows. The ability to seamlessly integrate related software items into a bank’s IT landscape, and exploiting the speed and capacity advantages brought about by technological advancements like in-memory, column-ori-ented database management systems is thus a key factor for success in this field.

7.2.4 Summary of Key Statements from QuestionnairesIn our survey, representatives of both regulatory agencies and auditors have identified the following list of new regulatory provisions which they regard as the main cost drivers for the future IT infrastructure in Banks:

• BCBS 239 (i.e. the Basel Committee’s guideline on Princi-ples for effective risk data aggregation and risk reporting)

• Basel III, • Dodd-Frank-Act,

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• The recommendations set forth in the Liikanen Report (i.e. the 2012 Report of the European Commission’s High-level Expert Group on Bank Structural Reform),

• MIFIR/ MIFID, EMIR, • Multi-curve valuations

Taken together, these developments point to a general need to gather and manage the information and processes required for accounting, solvency capital calculations, treasury opera-tions and risk, liquidity and funding management purposes in a common and consistent database for all regulatory and risk reporting requirements (see Principle 5 and Principle 7 (iii)). From the viewpoint of regulators and auditors, many banks today have a complex infrastructure which does not allow a sufficient degree of flexibility for the fulfillment of the new requirements. Their observation is that the IT infrastructures existing in many banks have evolved historically, and exhibit a very high degree of complexity. Notably in the large systemi-cally relevant banks, a timely shift to an entirely new and inte-grated framework is expected to bring about considerable cost and, at the same time, significant operational risk. What further complicates the tasks is that in the course of implementing the new framework, banks will have to keep step or catch up with the current changes in the existing one. However, the huge ini-tial investment implied by a move towards a common, integrat-ed system can be reasonably expected to result in significant cost reductions, particularly when keeping step with the new regulatory requirements. The experience gathered thus far has led to a widespread con-sensus concerning the question of whether systemically rele-vant banks would be better able to overcome existing bottle-necks within the existing IT infrastructure by enhancing legacy systems, or whether they should opt for an investment in a completely new and integrated system. There is a clearly ex-pressed viewpoint that a move to a new and integrated frame-work is the superior strategy.The rationale behind this line of reasoning is that existing weaknesses in the IT infrastructure of banks implies a severe susceptibility to error whenever the fulfillment of reporting du-ties requires the combination of data from different areas of op-eration. The most obvious example for the occurrence of such a situation is financial reporting, which requires the combination of accounting, regulatory capital, and risk-related data.Further bottlenecks arise due to the extended stress testing requirements set by recent changes in the regulatory envi-ronment. These new rules include, inter alia, the need to con-duct reverse stress tests, i.e. the simulation of scenarios which would threaten the sheer survival of the organization if they came true. Meeting these demands constitutes a formidable challenge in the field of data management and analytics, and places very high demand on the capacity, flexibility and speed of both the databases and the analytical procedures in use. Here regulatory bodies and auditors both pointed to the exist-ing deficiencies regarding the flexibility and the degree of au-tomation of current data analytics and risk calculations, partic-ularly in cases where several risk drivers, products, segments, or legal entities are concerned (see Principle 7 (vi))

Generally speaking, gaps in data availability and the need for more flexible tools for automated information processing were among the most central subjects discussed in the context of our study (see Principle 7 (v)). When asking the question, “In which sensitive and risk-related parts of banks’ IT infrastruc-ture regulators and auditors have recognized specific weak-nesses in the light of the new or refined supervisory rules?” the answers we received crystallized around the following points (see Principle 7 (iii)):

• Availability of product specific data and data analytics,• Legal entity views, and• Timeliness of financial data and risk analytics. This leads to the question of which processes and technolo-gies systemically relevant banks need in order to be capable of delivering data about all relevant risk and success factors to regulators and board members alike. In the following, we list the most important improvements demanded by regulatory authorities and auditors (see Principle 7):

• Implementation of a central data warehouse• Improvement of data and process governance• Introduction of more automated processes• Flexible and customized modules for automatic analysis,

stress scenario generation and ad hoc stress testing• Enhanced capabilities and data analytics for product valua-

tion and risk management calculations• Enhanced capabilities for legal entity- and jurisdiction-spe-

cific analytics

Given the background of new regulatory provisions and the general responsibility for business and risk strategy in the ICAAP process of banks, the central question arises how banks can inform their board members in an appropriate and timely manner when decisions have to be made under stressful con-ditions (see Principle 6 (v) and 7 (vi)). From the viewpoint of regulators and auditors, data availability and quality need to be improved, and the structure and transparency of risk reports must be enhanced to increase the speed and accuracy of the group wide reporting process in order to

• achieve timely availability of balance sheet information and scenario calculations (see Principles 6 (iii) and 7 (v) and (vi))

• enable product valuations in a multi curve environment (see Principle 7 (iv))

We also asked the question, “What information should be avail-able for management with regard to correlated shifts of rele-vant risk factors and their impact on an institution’s aggregat-ed risk position, and how detailed should this information be?” The answers contained the following issues (see Principle 7 (ii)):

• The impact of such shifts on the amounts of regulatory and economic capital required should be quantified on both the group level and for the individual business areas or segments

• Appropriate scenarios should be set up, and related simula-

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tions should be implemented• The outcome of the analysis must enable decision makers

to identify risk return profiles of individual products and customer relationships

We then asked what the respondents would, in the future, re-gard as an acceptable time lag for reporting the actual use of regulatory capital and economic capital on a consolidated group level. In response, the participants in the survey first em-phasized that the answer to this question generally depends on the type of business model and the risk profile of the particular bank under consideration. Nevertheless, all of our respondents from the regulatory authorities and from the auditors stated that for a transition period, institutions should aim for flash results within five business days and for final results within ten business days from the effective date, and that this recom-mendation applied to both regulatory and economic capital. Forward looking best practice for system relevant institutions accepted time lags will be one day.The next question asked to the representatives of superviso-ry authorities and auditors addressed the adequacy of current processes and technologies which banks apply for aggregating relevant risk factors from different subunits on a group level in near term. The answers given were somewhat disillusion-ing: The respondents estimated that, in most banks, a large percentage of the related processes currently implemented are insufficient to meet future requirements. From the perspective of regulators and auditors, another is-sue that received a very high level of attention is the effective, timely and precise information available to board members about the liquidity and risk profile of their institution (see Prin-ciples 6 (v) and 7 (vi)) . The availability of balance sheet data and product valuations in different scenarios, as well as liquid-ity forecasts for stress scenarios, is a key condition for meeting the requirements of the business and risk strategy, and fulfill-ing the expectations of investors. Moreover, the ability to “drill down” from highly aggregated figures to the level of line items, business areas, countries, and products is of utmost importance for understanding the causes of potential liquidity shortfalls. On the issue of designing systems and processes in order to ensure the delivery of real-time data on key Basel III ratios like Leverage Ratio, LCR, and NSFR, we received several answers. The most common ones stated that (see Principle 6 (iii) – (v))

• timely data availability is essential, • there is an increased need for integrated systems where

Basel III and accounting data can be easily accessed, so that the calculation of required results can be performed at the push of a button.

• input data need to be reconciled on the grounds of a single, well-defined source for all the data entities (the “golden” data source requirement).

Regarding the future, we received contradictory answers to the question regarding whether systemically relevant banks will have processes and technology in place that are capable of ag-gregating relevant risk factors like market or liquidity risks from

different subunits or individuals on a group level in real time. But we could infer the common perception that a time horizon of not more than one day will be the upper limit for these banks and best practice is real time (see Principle 6 (iii) and (iv)). Currently, a European Asset Quality Review Process, which is intended to prepare the Single Supervisory Mechanism in Eu-rope, is under way. We therefore want to highlight the opinions of regulators and auditors on regulatory and economic capital calculations on the one hand, and on risk monitoring across all asset classes on the banking book on the other. When en-quiring about how systems and processes should analyze and simulate potential effects of business decisions on Basel III key figures, or on regulatory and economic capital utilization, we received the answers below:

• There is a need to introduce modules and tools based on the consolidated data base (see Principle 5))

• Systems need to be both fast and flexible, and equipped with automated ad hoc stress testing capabilities (see Prin-ciples 6 and 7)

• In the near future, the scenario simulations need to be imple-mented on productive data, and the results will have to be integrated into the decision making process (see Principle 7)

• Balance sheet data and product valuations in a multi-curve environment must be available quickly (see Principle 7 (iv))

• Systems need to enable banks to identify the drivers of the demand for regulatory capital as well as economic capital. Forward-looking scenario calculations are of vital importance and must include sensitivity analyses of spe-cific risk and performance indicators for different business segments and bank products (i.e. profitability calculations for business areas under the conditions set by Basel III (see Principle 7 (ii))

The European Central Bank has announced that they will also potentially use the option to examine banks’ internal rating based models to check whether or not the calculated risk weights for specific positions on the banking books are suffi-ciently conservative. Based on this observation, we wanted to know how processes and technologies of banks should be de-signed to deliver a dynamically complete overview of the cor-related risk and return characteristics of different asset classes on their banking books (see Principle 8). The main areas where regulators and auditors see potential for improvement can be summarized as follows:

• Calculations should be more automated• In the design of systems, a clear distinction should be made

between systems that store information (product, risk data, finance data) and systems that do calculations (risk engines, finance calculations, product valuations).

• From front to back, the same stored data should be used. • Calculation results should again be stored in readily acces-

sible data warehouses• Trading book processes should be applied to the banking

book with adequately reduced frequency and data require-ments to keep costs under control.

43


To the question, “Which types of early warning indicators the risk management unit of a systemically relevant institution must have in place to fulfill regulatory requirements?” we re-ceived the answers listed below (see Principle 7 (vii)):

• VaR• Risk sensitivities• Risk specific stress testing results• Unsecured wholesale funding forecast • Risk measures according to trigger definitions in recovery

plan

Our investigation also focused on the capabilities of profes-sional providers of IT solutions for banks. Here, we started with the question about the most recognized bottlenecks in the IT infrastructure of banks, and inquired as to which areas of banks’ investments in innovative IT solutions should enjoy highest priority.A representative selection of answers is given below:

• The fragmented IT landscape, with different applications being used for the same task in different entities or busi-ness units, needs to be integrated and streamlined

• Data from a variety of sources must be reconciled (e.g. across legal entities or for different functions such as fi-nance and risk) and need to be integrated as well.

• There is a need for a consistent strategy applying to data storage, all the kinds of calculations required, and the acces-sibility of calculated data (e.g. valuations and sensitivities)

• An integrated view is needed regarding the requirements for regulatory reporting, financial reporting, risk manage-ment reporting, data reconciliation, and calculation. This applies for the group as a whole and for its business units across legal entities, potentially located in different ju-risdictions with individual regulatory requirements (e.g. CRDIV in Europe and CCAR in U.S.)

With this as a starting point, we asked where regulatory au-thorities and auditors see substantial gaps in the related solu-tions offered by professional providers. A representative selec-tion of answers is given below:

• Basel III reporting systems and software are too inflexible and do not provide analytic tools

• Multi curve valuation capabilities and hedge accounting engines are not available

• Real-time risk analytics are insufficient• There are cases where the availability of correct, complete and

granular product-specific data cannot be taken for granted.

When asking for typical examples of weaknesses on the side of professional providers, we received the answers below:

• Not all systems provide sufficient functionalities for multi curve valuation and hedge accounting

• Counterparty risk data are often incomplete and analytics too time consuming

• Product specific data are often incomplete in comparison to legal documentation (e.g. missing or incomplete informa-tion on optionalities or for the purpose of liquidity stress testing)

• Not all systems provide proper reconciliation capabilities across finance and risk functions

• There is often a considerable lack of flexibility as far as the integration into existing systems of banks is concerned.

• There is a lack of harmonization among the various mod-ules and solutions available for different reporting activi-ties, which complicates the comparison or the combination of data.

In a nutshell, we can state that our interviewees consider spe-cific requirements for IT infrastructures to be state of the art from a regulatory perspective. These are

• Automated ad hoc stress testing functionalities• A central data warehouse with reporting and analyzing

modules• Correct, complete, and granular product data• Timely balance sheet data• Timely and complete counterparty data for the entire bank

or group

There was a clear indication that any move towards overcoming these deficiencies should use BCBS 239 for further guidance.Banks, on the other hand, also highlighted that data integrity, data protection and cyber security are extremely important ca-pabilities for providers, and pointed out that not all profession-al providers have the level of capabilities required by banks in these areas of activity. Apart from that, they placed great em-phasis on the need to integrate external products and services deeply within their proprietary, internal software and hardware platforms as well as with their operational processes, and to do so in a timely manner. It was found that external products and services can rarely be integrated into banks’ environments without some degree of customization or optimization.When being asked about the most important bottlenecks in their IT infrastructure, and which business units will need to give innovative IT solutions the highest priority, banks gave a broad range of answers. Two representative statements from the banks with global systemic relevance were as follows:

• Particular to those banks with a global playing field, the scale, diversity and complexity of business models is the biggest challenge for IT infrastructures.

• The IT Infrastructure team must attain a balance between time to market (agility, responsiveness and customization), efficiency (standardization, automation, productivity) and risk management (security, data protection, access man-agement, etc.). Each of these can be bottlenecks in their own way if not managed proactively and in close partner-ship with business leadership.

We asked banks representatives about the types of early warn-ing indicators which the risk management unit of their respec-

44


tive institution is working with, and got a very broad range of answers. In general, banks monitor a variety of risk indicators, depending on the type of risk and the nature of the related business activity. Examples by risk type include:

• In the field of credit risk, the quantities examined include the size and composition of portfolio, industry-specific and geographical exposure concentrations, net charge-off rates, as well as maturity and ratings profiles across asset types. Stress tests also form a regular part of the related analyses.

• Market risk measurement was carried out by examining the average, minimum and maximum of value at risk by portfo-lio and product, through VaR back-testing (which consists of comparing historical frequency counts of extreme loss events to model prediction), and debit valuation. Here, too, standard model results are often supplemented by stress test outcomes.

• Country risk is usually evaluated by country-specific total exposure.

• Liquidity risk is examined by assigning projected cash flows to maturity ranges and with the help of funding terms.

Many companies – even includ-ing global market leaders - do not currently calculate a for-ward view of economic capital in a way that reflects changes in business decisions

The new regulatory framework now requires every institution to have a procedure in place for planning its future capital re-quirements. It thus places a much greater emphasis on cap-ital planning. In their internal processes intended to secure their risk-bearing capacity, institutions must analyze the way in which intended modifications to their own business activ-ities or strategic objectives, along with expected changes in the economic environment, are expected to impact their future risk-bearing capacity. In order to identify future capital require-ments as early as possible, a period extending beyond the risk analysis horizon of the risk-bearing capacity concept (which usually equals one year) must be covered. The capital planning procedure should thus apply to a time period of several years. This should add a stronger, future-oriented component to the concept of risk-bearing capacity, and enable institutions to im-plement necessary corporate actions early.Therefore, institutions have to work with plausible assump-tions regarding the development of risks. At the same time, the analysis must account for the possible occurrence of unex-pected adverse developments that would be detrimental for

the institution. The fulfillment of this task enables institutions to anticipate the impacts on capital resources and require-ments that would result, if previous expectations regarding the magnitude of risks and the risk-taking potential turned out to be too optimistic.As a consequence, banks are working on firm-wide forecasting and capital stress testing processes and systems in order to enable a forward looking view that reflects the impact of busi-ness strategy, portfolio evolution, and market dynamics on the projections of regulatory capital. Moreover, many companies – even including global market leaders - do not currently calculate a forward view of econom-ic capital in a way that reflects changes in business decisions. When being asked the question which processes and technol-ogies are in place to deliver a dynamically complete invest-ment picture that provides a correlated look across the risk and return profiles of different asset classes on their banking books, many firms referred to their internal capital manage-ment processes. Typically, banks utilize a capital attribution approach that in-corporates Basel III RWA, capital and other applicable regula-tory requirements and economic factors at the asset/liability and exposure levels, as well as at the business line level. The goal thus pursued is to facilitate transaction level and busi-ness line level return analysis across the banking book and trading book activities. The question about the availability of real time data was an-swered negatively by a majority of the interviewees addressed. In general, aggregated data are available in within pre-defined time frames for each risk type. However, some of the global market leaders in Europe and the US stated that even real-time risk information is available to risk executives to facilitate de-cision making. Basel III ratios in general are not required to be measured on a real-time basis. The majority of respondents state that daily computation of the aggregate firm-wide Basel III metrics is currently available in the systems or will be targeted in the near future.The general standard is to report the Liquidity Coverage Ratio on a monthly basis. Liquidity risk assumptions and values are collected from underlying business line and legal entity data with broadly varying levels of automation.Banks do, however, run liquidity stress tests incorporating market shock scenarios with the intention to calibrate (among others) monetization value of unencumbered collateral. Also, at least in the setup used by global market leaders, behavioral patterns of market participants during different types of stress events are incorporated in liquidity stress tests. In addition, a broad range of monitoring metrics is in place for the analysis of bank-specific and system wide liquidity trends (see Principle 6). These include

• CDS spreads,• 10 year cash prices,• Stock prices,• Deposit outflows,• Cash balance changes,

45


• Increases in tri-party haircuts,• Changes of margin requirements in derivatives trading,• Secured funding volumes and weighted average maturities• Commitment draws• Stress test metrics (both internally defined as well as regu-

latory defined), and• Long-term debt maturities

There is widespread consensus that having a unified data struc-ture across market and credit data is important to facilitate in-tegrated approaches for pricing and risk calculations. Howev-er, firms differ considerably in the extent to which they have reached this target.Looking forward to a potential implementation of the require-ments summarized in the BSBS paper “Fundamental Review of the trading book” published in June 2012, banks declared that additional data and analytical requirements are necessary for the ability to calculate additional capital requirements for in-struments on the trading book that have increased liquidity risk in a stress scenario. The items required include (see Principle 7)

• Historical data for trading positions, market prices, and oth-er reference information,

• A framework for stress analytics designed to assess the im-pact of market dynamics on trading positions,

• Additional stress analytics for testing the market-related risks incorporating multiple scenarios assuming changes in risk factors such as credit spreads, equity prices, interest rates, currency rates, and commodity prices, and

• Sensitivity measures that form an integral part of the firm’s capital stress testing processes and provide a dynamic view of capital requirements in various economic scenarios.

We also asked a question about the main adaptations banks will have to make in their existing risk infrastructure if a move from Value at Risk to Expected Shortfall becomes mandato-ry. Here, at least the large players declared that their systems have the flexibility to keep the level of adaptions low. One bank even declared that they are already quantifying risk using the expected shortfall method, and that they do this by averag-ing over the worst daily returns observed long-term in histori-cal time series. The same company explained that they would not expect risk infrastructure to be impacted by any potential regulatory requirement to break down approval processes for internal models on the trading desk level, because the Firm’s infrastructure is currently able to support related models at a variety of levels.When asking the question – which functionalities and analytics a group wide liquidity management system linked to a central management cockpit/dashboard should provide – we received the answers below (see Principle 6 (v)):

• Liquidity risk appetite of key operating entities• Stress test results of key operating entities• Liquidity limits, indicators and metrics of key operating entities• Unencumbered available securities by Collateral type and

location

• Key balance sheet and off-balance sheet trends• Currency risk• Intraday liquidity• Regulatory metrics

One of the greatest challenges to supporting senior manage-ment in real-time decisions is to ensure a thorough understand-ing of the most important key indicators required for monitor-ing and reporting. Recent advances in the capabilities of end user devices (e.g. touch screen, enlargement and shrinking functions, mobile connectivity) can greatly facilitate the at-tainment of this goal. The next challenge is sourcing the data in such a way that it is both highly accurate and easily obtain-able with minimal disruption to core processing platforms. The process then needs to have regular checkpoints to verify the relevance and timeliness of the information presented so it can be updated when needed.

46

Conclusion of the Banking Study | Banking Study

Banks have no choice but to comply with the current and on-going changes in their regulatory environment and to adapt to megatrends changing the economic fundamentals for financial institutions. Identified key drivers for fundamental adaption in business mod-els and organizational frameworks of banks are changes in the regulatory framework and the offered business opportunities by a steep innovation curve in modern IT-Technologies.To be successful in differentiating their business models from those of their competitors, banks with a global business set up will need strong distribution and communication channels for innovative and competitive financial services. This is of special importance for growing markets in the emerging countries as traditional distribution of banking products is playing a subor-dinated role whereas innovative channels like mobile banking are becoming more and more dominant there.For the European markets we are not expecting an overall growth of the demand for financial services but a potential redistribution of market shares. Because of trends such as the European Corpo-rate Funding disintermediation, traditional business areas such as the loan business have become extremely competitive and thus have weak margins. For a credible growth story in matured markets partially those such as Europe, characterized by being overbanked, banks need a clear strategy to make their platforms and distribution channels superior to those of their competitors. To be a successful player in the global financial markets such as in the non-standardized OTC derivative markets, banks do not only require sufficiently high risk bearing capacities. Rather, they also need a technological platform for the fast pricing and hedg-ing of products, and for the calculation of relevant risk figures like the Credit Value Adjustment. For the standardized deriva-tive markets characterized by Central Clearing, we expect that the majority of transactions will be executed by pure electronic trading, and in line with this, there will be a further competition of electronic trading platforms with optimized response times in combination with better pre and after sale and trade services for the clients. So stronger technological platforms and enhanced risk-bearing capacity will be key for the role of market makers in the newly regulated global derivatives markets as well as in the global equity, bond, and commodity markets.We are expecting similar developments in other parts of the financial markets and services for client groups like Corporates, Institutional Investors, Municipalities or the coverage of High Net Worth Individuals (HNWIs) and Family Offices.Establishing a modern state of the art service platform in com-bination with a powerful risk and liquidity management infra-structure creates high upfront costs in a time period where the business models of banks becomes more expensive because of increasing regulatory and risk management costs driven by new Basel III rules and many other initiatives of supervisory authorities. In order to mitigate these costs and ensure attractive economies of scales, banks need a credible growth story. This looks like a circular argument as we have mentioned already

that the establishment of a growth story needs high upfront investments in state of the art technological infrastructures as prior condition. And it is indeed true that in a world character-ized by emerging markets with growing financial sectors on the one hand and matured markets with massive impacts on banks business models because of dramatically changing regulatory requirements on the other, the future market share of banks will be determined by successful change management. And it is also true that the bottleneck for this success will be available resources such as risk capital and risk bearing capacity, liquidity and profitability, in order to mitigate the upfront investments required for a successful transformation of existing business models. On this basis we summarize that risk management ca-pabilities and innovative distribution channels and service plat-forms will be the key competitive factors for the future. At the same time it is clear that prerequisite for being a leader are high upfront costs which will be compensated later by better econ-omies of scale and reduced fixed costs achieved by increased automation and improved value chains.Banks and auditors in Europe and the USA have a similar view on these challenges and the key factors for successful innovation and change management. However the environment and the initial position for European and US-Banks are quite different. In the US a few large, global banks characterize the banking market together with a huge and already profitable home mar-ket. US banks also have a profitable business model and it is evident that the U.S. banks use the resources available to them efficiently and increase their technological dominance together with stronger capital base and increased risk bearing capacity to gain market share both in the global equity, bond and derivatives markets, as well as in the fast-growing retail markets in the emerging economies. In our view this will strengthen the U.S. dominance in the global capital markets in the Post-Crisis-phase with the main competitors coming from Asia. European banks do not have resources comparable to their U.S. competitors. Often the balance sheet restructurings necessary after the crisis are not finished and the size of the banking sector compared to the size of the economy is less favorable in Europe than in the US. Most examples so far of successful expansions of banks in new business fields involving costly use of risk capital, ad-vanced technology, and professional staff to build a competitive platform, have come from banks located in a profitable home market, for example Barclays in the UK. The public and political pressure on banks in Continental Europe is significant and not all constructive. Concerns about the future global role of Europe in an important key industry are under-represented in the debate. From our view Europe faces the risk that a redistribution of finan-cial market shares and the financial industry of the future will be dominated by U.S. banks and its Asian competitors. At the same time, low-profit banks without adequate business models are also a threat to the stability of the financial markets. A one-sid-ed view for stricter regulation, without taking into account the prerequisites for profitability also poses a danger.

8 CONCLUSION OF THE BANKING STUDY

47

Conclusion of the Banking Study | Banking Study

is professor of Financial Risk Management at the Frankfurt School of Finance & Management. Previous-ly, he held various executive positions in the financial industry. Martin holds a PhD in mathematics and has published on credit risk modeling and portfolio optimization in several scholarly journals including Quantitative Finance and the Journal of Theoretical and Applied Finance.E-mail: m.hellmich[at]fs.de

Prof. Dr. Martin Hellmich

joined the Frankfurt School of Finance & Management in October 2013 as a managing director for the BaFin licensed Frankfurt School Financial Services GmbH. In addition, he is the General Manager for the risk- and regulation subsidiary company SCDM Germany GmbH. He is a certified “Chartered Alternative Investment Analyst” and holds a bachelor degree in Business Administration from the Frankfurt School of Finance & Management.E-mail: b.schuck[at]fs.de

Bjoern Schuck

joined the Frankfurt School of Finance & Management as a lecturer in 2013, after having gathered sev-eral years of related professional experience in the fields of banking and asset management. He holds a doctoral degree in economics from the University of Konstanz and is author and co-author of several articles in the fields of economics and finance. Email: s.siddiqui[at]fs.de

Dr. Sikandar Siddiqui

is the Julius Schlesinger Professor of Operations Management and Chair of the department of Informa-tion, Operations and Management Sciences at New York University Leonard N. Stern School of Business. His research focuses on the modeling of production and service systems, and recently also on opera-tional risk in financial services. He has both written and co-written numerous technical papers on these topics and is editor and associated editor of several professional journals.E-mail: mpinedo[at]stern.nyu.edu

Prof. Dr. Michael Pinedo

9 AUTHORS

is head of the Center of Excellence for Business Innovation within Business Transformation Services at SAP. He is also the president of the Business Transformation Academy (BTA), a global think tank organ-ized as a Swiss non-profit organization. Sine 2009 Uhl has been a professor at the University of Applied Sciences and Arts Northwestern Switzerland (FHNW).E-mail: a.uhl[at]sap.com

Prof. Dr. Axel Uhl

48

Appendix | Banking Study

Mega-Trends

Risk & Compliance

A-1Mega-Trends What business and technology challenges are closely intertwined?

Answer:

A-2Mega-Trends What strategic role should risk management have in a banking institution and what

role should innovative IT play in its implementation?

Answer:

A-3Mega-Trends

In your opinion, what are the most important and challenging new regulatory requirements for banks? What areas do you expect to be the focus of future regularly refinements? How can process innovation help to meet these requests?

Answer:

A-4Mega-Trends In what manner will IT budgets change in order to keep pace with new regulatory demands?

Answer:

A-5Mega-Trends What potential do you see for banking in the increasing availability and growing analytics

capacity for big data and real time data?

Answer:

A-6Mega-Trends What risk/challenges do you see in the use of big data and real time data?

Answer:

A-7Mega-Trends What areas do you think can be positively impacted by the use of Big Data technology?

Answer:

A-8Mega-Trends Which part of the ICAPP process do you think can be positively impacted by the use of

Big Data technology?

Answer:

B-1Risk & Compliance What are general IT-infrastructure requirements for national or international system relevant

banks in the new regulatory framework?

Answer:

B-2Risk & Compliance Starting with your existing IT infrastructure, which new regulatory rules are the biggest

cost drivers from an IT perspective?

Answer:

B-3Risk & Compliance In which sensitive and risk relevant parts of banks’ IT infrastructure do you recognize specific

weaknesses which will be addressed under new or refined supervisory rules?

Answer:

B-4 Risk & ComplianceWhat employees, processes, and technologies do risk relevant banks need, in order to be capable of delivering data about all relevant risk and success factors to regulators and board members? What improvements do you see? What improvements do you suggest?

Answer:

Regulator Survey

10 APPENDIX

49


B-5Risk & Compliance

What are the bottlenecks in banks for fulfilling stress test and reverse stress test requirements in terms of Data management, analytics capacity, required flexibility and speed requirements?

Answer:


Based on your supervisory experience, are system relevant banks better able to solve their bottlenecks with existing IT infrastructure by enhancing legacy systems or should they choose to invest in a completely new and integrated framework?

Answer:

B-7Risk & Compliance How can relevant banks appropriately inform their board members in a timely manner with

regards to decision making in stress scenarios? What improvements are necessary?

Answer:

B-8Risk & Compliance How can and should systems and processes analyze and simulate potential effects of busi-

ness decisions on Basel III key figures or on used regulatory and economic capital?

Answer:


How should processes and technologies of banks be designed to deliver a dynamically com-plete investment picture that provides a correlated look across the risk and return spectrum of different asset classes on their banking books? Where do you see this improving?

Answer:

B-10Risk & Compliance What information should be available for management in case of correlated shifts of relevant

risk factors for an institution's aggregated risk position? How detailed should they be?

Answer:

B-11Risk & Compliance How capable are the processes and technologies that banks have in place to aggregate

relevant risk factors from different subunits on a group level in real-time?

Answer:


What is the short notice availability of detailed information concerning correlated shifts of relevant risk factors regarding aggregated risk positions for the management of large banks with complex business models? Where do you see improvements?

Answer:


What do you think about the following statement?

“The ability to store, process, use and re-use risk relevant information and from all sources quickly and to make it accessible anywhere from multiple devices in combination with proactive ‘what if’ capabilities will be absolute necessary in the future for a financial institu-tion being system relevant on a national or international basis?”

Answer:

B-14Risk & Compliance What is the importance of board members being effectively informed about the liquidity

and risk profile of their institution?

Answer:

Regulator Survey

50


B-15Risk & Compliance Which long-term liquidity ratios should be chosen by the banks to address structural liquidity

risks, liquidity mismatches and net stable funding sources?

Answer:

B-16Risk & Compliance Which specific features in terms of liquidity measures, scenario simulations, specific reporting

and forecasting, or other capabilities are essential?

Answer:

B-17Risk & Compliance How important is the drill-down from highly aggregated figures to the line item/product/

country/all dimensions to understand the cause of liquidity gaps?

Answer:

B-18Risk & Compliance How should systems and processes be designed to deliver real time data about Basel III key

ratios like Leverage Ratio?

Answer:

B-19Risk & Compliance What are the general future requirements regarding data availability for board members who

are fully responsible for business and risk strategy?

Answer:

B-20Risk & Compliance In what ways do you anticipate system relevant institutions will have processes and technol-

ogy in place to support management decisions and responses in stress scenarios?

Answer:

B-21Risk & Compliance In what ways do you anticipate system relevant institutions will have processes and technol-

ogy in place to support management decisions and responses in stress scenarios?

Answer:


In what ways do you anticipate system relevant institutions will have processes and technol-ogy in place capable to deliver correlated views on risk factors and their cumulative impact on the organizational risk profile?

Answer:


On which basis should it be possible for the management of a system relevant institution to obtain detailed information concerning correlated shifts of relevant risk factor regarding said institution’s aggregated risk position and what is the acceptable time delay?

Answer:


Do you expect that in the future banks will have processes and technology in place capable of delivering a dynamically complete investment picture that provides a correlated look across the risk and return spectrum of different asset classes in their banking book?

Answer:

B-25Risk & Compliance In the future, what will be the accepted time lag for reporting the actual use of regulatory

capital on a consolidated group level? Same question, but at an economic, risk level.

Answer:

Regulator Survey

51



In the future, do you expect risk relevant banks to have processes and technology in place ca-pable of aggregating relevant risk factors like market or liquidity risks from different subunits or individuals on a group level in real time?

Answer:

B-27Risk & Compliance Which types of early warning indicators should the risk management of a system relevant

institution have in place to fulfill regulatory requirements?

Answer:

B-28Risk & Compliance What adaptations are required from banks for the promptness of reporting risk:

more intra-day, real-time reporting, on-demand drill-down?

Answer:

B-29Risk & Compliance What will be the specific requirements for reporting quality and frequency for banks concern-

ing Basel III key ratios, such as Leverage Ratio, LCR, and NSFR?

Answer:

B-30Risk & Compliance What will be the specific requirements for banks’ reporting quality and frequency for banks

concerning new securitization rules?

Answer:


What will be the specific requirements for banks’ reporting quality and frequency for banks concerning new rules for trading book and market risk? (Stressed value at risk, Incremental risk charge, Comprehensive Risk Measure, Effective Expected Positive Exposure, Stressed EPEs, Specific wrong way risks, Credit Value Adjustment, standardized/advanced CVA charges)

Answer:


What will be the accepted time delays for the reporting of the following: Liquidity Measures, Changes in the Risk Bearing Capacity, Use and exceeding of limits for market and credit risk, Change of the credit quality of large and million loans, Use of economic and regulatory capital

Answer:

B-33Risk & Compliance In what manner will IT budgets change in order to keep pace with new regulatory require-

ments concerning risk and liquidity management?

Answer:

B-34Risk & Compliance Which parts of system relevant banks have the highest requirements for improving the cur-

rent status of their processes and IT systems?

Answer:

B-35Risk & Compliance In which risk relevant part of system relevant banks you see potential applications for

advanced IT solutions like In-Memory-Technology?

Answer:

Regulator Survey

52


Capabilities of Providers

B-36Risk & Compliance From a regulatory perspective, in which areas do you see real time data as a necessity?

What are the minimum system requirements for banks?

Answer:

C-1Capabilities of

ProvidersWhere do you see substantial gaps in solutions for the functions described above being offered by professional providers?

Answer:

C-2Capabilities of

Providers Can you give typical examples for weaknesses of these professional providers?

Answer:

C-3Capabilities of

Providers Are there any of these weaknesses which are in all professional systems?

Answer:

C-4Capabilities of

Providers

What are the sensitive parts of a system relevant banking organization where identification, assessment, and management of the inherent risk in real time are a big advantage, or even a must, despite additional costs?

Answer:

C-5Capabilities of

ProvidersWould it make sense to offer a conference here to discuss these types of weaknesses in detail and potential solutions?

Answer:

C-6


Do you have specific requirements for IT-infrastructures in mind being state of the art from a regulatory perspective? From a regulatory perspective, what specifications and capabilities would make an IT infrastructure state of the art?

Answer:

C-7Capabilities of

ProvidersWhat are the most recognized bottlenecks in the IT infrastructure of banks and in which areas must banks invest in innovative IT solutions with highest priority?

Answer:

Regulator Survey

53


Mega-Trends


Answer:

A-2Mega-Trends How would you describe the strategic role of risk management in your institution? What role

does innovative IT play in the implementation of this strategy?

Answer:

A-3Mega-Trends Does innovative information technology in general play a strategic role in your institution?

How would you describe your strategy in this area and what major challenges do you face?

Answer:

A-4Mega-Trends What will your ‘Brand Promise’ be – how do you differentiate yourself from your competitors?

Answer:

A-5Mega-Trends What will drive change and adaptation of your business model in the next 3-5 years?

Answer:

A-6Mega-Trends How can process innovation help to meet regulators requests, increase revenues, enhance

customer satisfaction, and reduce costs?

Answer:

A-7Mega-Trends What role do new technologies play in transforming banking to a more client centric business

model?

Answer:

A-8Mega-Trends How much are IT budgets expected to increase in order to keep pace with new regulations

and changes to your business model?

Answer:

A-9Mega-Trends

In what ways will the introduction of Dodd-Frank affect existing business fields and revenue sources in the future? Which new business fields and revenue sources are triggered by this change?

Answer:

A-10Mega-Trends What modifications to your IT-infrastructure will be necessary to realize these opportunities?

Answer:

A-11Mega-Trends

What will the impacts of the mandatory clearing by a central counterparty for some major classes of derivatives on your business and fee models as well as on collateral optimization practices be?

Answer:

A-12 Mega-Trends What role do you anticipate Multi Dealer Platforms and Organized Trading Facilities will play in your future business and fee models?

Answer:

Banking Survey

54


Risk & Compliance

A-13Mega-Trends As the availability and capacity for robust analytics increases, what potential role do you see

for big data and real time data in banking?

Answer:

A-14Mega-Trends What business analysis could be possible by leveraging big data in the short-term?

Answer:


Answer:


Answer:

A-17Mega-Trends What potential do you see for In-Memory-Technology and cloud computing for your

organization?

Answer:

B-1Risk & Compliance Starting with your existing IT infrastructure, which new regulatory rules are the biggest cost

drivers from an IT perspective?

Answer:

B-2Risk & Compliance What weaknesses do you see in your risk management systems and IT infrastructure?

Answer:


Do you see future improvements, in terms of employees, processes, and technologies, nec-essary to be capable of delivering data concerning all relevant risk and success factors to regulators and board members? What improvements would you suggest?

Answer:

B-4Risk & Compliance What types of early warning indicators does the risk management of your institution work

with?

Answer:

B-5Risk & Compliance How are early warning indicators implemented in existing IT-infrastructure?

Answer:

B-6Risk & Compliance How can your current systems and processes analyze and simulate potential effects of busi-

ness decisions on Basel III key figures or on used regulatory and economic capital?

Answer:

B-7Risk & Compliance Complex Event Processing: How do your processes and systems ensure your capability for

real-time detection of data and process patterns?

Answer:

Banking Survey

55



How do you guarantee that processes and technologies are in place to deliver a dynamically complete investment picture that provides a correlated look across the risk and return spectrum of different asset classes on your banking book?

Answer:

B-9Risk & Compliance What information should be available for management in case of correlated shifts of relevant

risk factors for an institution's aggregated risk position? How detailed should they be?

Answer:

B-10Risk & Compliance How capable are the processes and technologies you have in place to aggregate relevant risk

factors from different subunits on a group level in real-time?

Answer:


How available in the short term is detailed information regarding correlated shifts of relevant risk factors regarding aggregated risk positions to your management? In which cases is this information sufficient and where should it be augmented?

Answer:


What do you think about the following statement?

“The ability to store, process, use and re-use risk relevant information and from all sources quickly and to make it accessible anywhere from multiple devices in combination with proactive ‘what if’ capabilities will be absolute necessary in the future for a financial institu-tion being system relevant on a national or international basis?”

Answer:

B-13Risk & Compliance How can your systems and processes deliver real time data about Basel III key ratios like

Leverage Ratio?

Answer:

B-14Risk & Compliance Which kind of longer-term liquidity ratios do you have in place to address structural liquidity

risk, liquidity mismatches and net stable funding sources?

Answer:

B-15Risk & Compliance How do you deliver real time data about Basel III key ratios like NCR and NSFR?

Answer:

B-16Risk & Compliance What are the current reporting practices to meet the demands of these two distinct liquidity

risk horizons?

Answer:

B-17Risk & Compliance Which specific features in terms of liquidity measures, scenario simulations, specific reporting

and forecasting or other capabilities are you using?

Answer:

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B-18Risk & Compliance How does your institution assess the interaction of liquidity risk with other risk types, such

as market and credit risk?

Answer:

B-19Risk & Compliance How do your systems and processes drill-down from highly aggregated figures to the line

item/product/country/all dimensions to understand the cause of a liquidity gap?

Answer:

B-20Risk & Compliance What combination of monitoring metrics do you have in place for the analysis of bank-specific

and system wide liquidity trends?

Answer:

B-21Risk & Compliance Is the availability of unified data structures and risk systems for market and credit data

important for being able to deliver an integrated approach for pricing and risk calculation?

Answer:


What potential improvements have you identified in your risk infrastructure and pricing engines as being capable of delivering simultaneous valuations of derivative positions and counterparty risks?

Answer:

B-23Risk & Compliance What challenges do you anticipate banks' IT-infrastructures facing, with regards to the setup

of CVA-desks managing counterparty risk for derivative positions at a bank wide level?

Answer:

B-24Risk & Compliance What are the main adaptations you will have to implement in your existing risk infrastructure

if a move from Value at Risk to Expected Shortfall becomes mandatory?

Answer:


What additional data and analytical requirements are necessary for the capability to calculate additional capital requirements for instruments on the trading book with increased liquidity risk in a stress scenario?

Answer:

B-26Risk & Compliance What impact on your risk infrastructure do you expect by a potential regulatory requirement

of breaking down approval processes for internal models on the trading desk level?

Answer:


Which specific improvements in risk management practices are necessary for the described adaptions and changes of business model in the future and what is the role of advanced information technology here?

Answer:

B-28Risk & Compliance What general future requirements for data availability are necessary for board members

being fully responsible for business and risk strategy?

Answer:

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B-29Risk & Compliance How can a bottom-up approach be computationally feasible for a large banking institution?

Answer:

B-30Risk & Compliance What functionalities and analytics should a group wide liquidity management system linked

to a central management cockpit/dashboard provide in your opinion?

Answer:


In which way will you have processes and technologies in place to be capable of delivering a dynamically complete investment picture that provides a correlated look across the risk and return spectrum of different asset classes on your banking book?

Answer:

B-32Risk & Compliance How can board members be effectively informed about the current liquidity and risk profile

of your institution?

Answer:

B-33Risk & Compliance How should processes and systems be designed to support senior management in real-time

decisions? What potential improvements do you see?

Answer:

B-34Risk & Compliance What adaptations are required from your side for the promptness of reporting risk: more

intra-day, real-time reporting, on-demand drill-down?

Answer:

B-35Risk & Compliance How could you improve the reporting quality and frequency concerning Basel III ratios like

Leverage Ratio, LCR and NSFR?

Answer:

B-36Risk & Compliance Are there any plans in your institution for implementing innovative new information

technology to enhance reporting and analytical capabilities?

Answer:

B-37Risk & Compliance What budget increases for IT do you expect to cope with the increasing regulatory

requirements concerning risk and liquidity management?

Answer:

B-38Risk & Compliance Which business units will require the most effort for improving the current status of process-

es and IT systems?

Answer:

B-39Risk & Compliance In which risk relevant part of your bank do you see potential applications for advanced IT

technology like In-Memory-Technology?

Answer:

Banking Survey

58


C-1Capabilities of

ProvidersWhere do you see substantial gaps in solutions for the functions described above being offered by professional providers?

Answer:

C-2Capabilities of

Providers Can you give typical examples for weaknesses of these professional providers?

Answer:

C-3Capabilities of

Providers Are there any of these weaknesses which are in all professional systems?

Answer:

C-4Capabilities of

ProvidersWould it make sense to offer a conference here to discuss these types of weaknesses in detail and potential solutions?

Answer:

C-5Capabilities of

ProvidersWhat are the most recognized bottlenecks in your IT infrastructure and which business units must invest into innovative IT solutions with highest priority?

Answer:

D-1Mobile Banking Are mobile banking and social network channels playing a different role in non-traditional

markets such as emerging markets?

Answer:

D-2


Given the current trend of client centricity, what role do you see for mobile banking in the future?

Answer:

D-3Mobile Banking Given the emergence of services provided by non-banking institutions such as mobile pay-

ment systems, what is your strategy in this area?

Answer:

D-4Mobile Banking In which areas do you see most potential for mobile IT solutions and what is your institution’s

vision for it?

Answer:

Banking SurveyCapabilities of Providers

Mobile Banking

59


Bank Survey African BanksMega-Trends


Answer:

A-2Mega-Trends What will your ‘Brand Promise’ be – how do you differentiate yourself from your competitors?

Answer:

A-3Mega-Trends What will drive change and adaptation of your business model in the next 3-5 years?

Answer:

A-4Mega-Trends Where do you see most process innovation being required?

Answer:

A-5Mega-Trends What is the likely trend on IT costs and why?

Answer:

A-6Mega-Trends Which customer forces do you see driving technology choices?

Answer:

A-7Mega-Trends What potential do you see for banking in the increasing availability and growing analytics

capacity for big data and real time data?

Answer:


Answer:


Answer:

A-10Mega-Trends What potential do you see for In-Memory-Technology and cloud computing for your organiza-

tion?

Answer:

B-1Risk & Compliance Starting with your existing IT infrastructure, which new regulatory rules are the biggest cost

drivers from an IT perspective?

B-2Risk & Compliance What weaknesses do you see in your risk management systems and IT infrastructure?


Do you see future improvements, in terms of employees, processes, and technologies, nec-essary to be capable of delivering data concerning all relevant risk and success factors to regulators and board members? What improvements would you suggest?

Answer:

Risk & Compliance

60


B-4Risk & Compliance What types of early warning indicators does the risk management of your institution work

with?

Answer:

B-5Risk & Compliance How are early warning indicators implemented in existing IT-infrastructure?

Answer:

B-6Risk & Compliance How should processes and systems be designed to support senior management in real-time

decisions? What potential improvements do you see?

Answer:

B-7Risk & Compliance Complex Event Processing: How do your processes and systems ensure your capability for

real-time detection of data and process patterns?

Answer:

B-8Risk & Compliance How can board members be effectively informed about the current liquidity and risk profile

of your institution?

Answer:

B-9Risk & Compliance How does your institution assess the interaction of liquidity risk with other risk types, such

as market and credit risk?

Answer:

B-10Risk & Compliance Which kind of longer-term liquidity ratios do you have in place to address structural liquidity

risk, liquidity mismatches and net stable funding sources?

Answer:

B-11Risk & Compliance How can a bottom-up approach be computationally feasible for a large banking institution?

Answer:


Which business units will require the most effort for improving the current status of process-es and IT systems? proactive ‘what if’ capabilities will be absolute necessary in the future for a financial institution being system relevant on a national or international basis?”

Answer:


Bank Survey African Banks

C-1Capabilities of

Providers Can you give typical examples for weaknesses in the offering of professional providers?

Answer:

C-2Capabilities of

Providers Would it make sense to run a conference exploring potential solutions?

Answer:

C-3Capabilities of

ProvidersWhat are the most recognized bottlenecks in your IT infrastructure and which business units must invest into innovative IT technology with highest priority?

Answer:

61


1

How important is Information Technology in your institution’s strategy?

Not important Very important

¡ ¡ ¡ ¡ ¡

2

Can process innovation and IT help to meet regulators requests, increase revenues, enhance customer satisfaction and reduce costs?

Not at all To a large extent

Meet regulators requests ¡ ¡ ¡ ¡ ¡

Increase revenues ¡ ¡ ¡ ¡ ¡

Enhance customer satisfaction ¡ ¡ ¡ ¡ ¡

Reduce costs ¡ ¡ ¡ ¡ ¡

3

Of which importance will the management of Big Data and real-time data be for banking?


Management of big data ¡ ¡ ¡ ¡ ¡

Management of real time data ¡ ¡ ¡ ¡ ¡

4

To which extend are current systems and processes you have in place capable to analyze and simulate potential effects of business decisions on various key figures in real-time?


LCR and NSFR ¡ ¡ ¡ ¡ ¡

Economic capital ¡ ¡ ¡ ¡ ¡

Regulatory capital ¡ ¡ ¡ ¡ ¡

Leverage Ratio ¡ ¡ ¡ ¡ ¡

Leverage Ratio ¡ ¡ ¡ ¡ ¡

Electronic Survey

62


5

How important are the following aspects of systems and processes in order to support senior management in its decisions?


Real-time analytics ¡ ¡ ¡ ¡ ¡

On-demand drill-down functionality ¡ ¡ ¡ ¡ ¡

Aggregation and comprehensiveness ¡ ¡ ¡ ¡ ¡

Simulation and Stress Testing ¡ ¡ ¡ ¡ ¡

6

To which extend are processes and technologies you have in place capable to aggregate relevant risk factors from different subunits on a group level in real-time?


¡ ¡ ¡ ¡ ¡

7

How important do you expect the following innovative new information technologies to be for your institution in the future?


In-memory technology ¡ ¡ ¡ ¡ ¡

Cloud computing ¡ ¡ ¡ ¡ ¡

Mobile computing ¡ ¡ ¡ ¡ ¡

8

How big are the gaps in solutions from professional providers concerning risk management, liquidity management and regulatory requirements?

Not at all To a large

Risk management ¡ ¡ ¡ ¡ ¡

Liquidity management ¡ ¡ ¡ ¡ ¡

Regulatory requirements ¡ ¡ ¡ ¡ ¡

Electronic Survey

63


9How important will mobile banking be in banking in the next decade?


¡ ¡ ¡ ¡ ¡

10How do you expect your institution’s budget for Information Technology to develop over the next 3 years?

Decrease by more than 25%

Decrease up to 25%

Stable Increase up to 25%

Increase by more than 25%

¡ ¡ ¡ ¡ ¡

Electronic Survey

64


Q1 Q2 Q3

ANSWERS MEET REGULA-TORS REQUEST

INCREASE REVENUES

ENHANCE CUSTOMER SATISFACTION

REDUCE COSTS

MANAGEMENT OF BIG DATA

MANAGEMENT OF REAL TIME DATA

1 1 2 3 2 4 0 02 8 6 20 9 14 5 43 13 30 54 40 46 21 414 94 96 93 100 87 99 745 114 95 59 78 77 104 108

NA 0 1 1 1 2 1 3Sum 230 230 230 230 230 230 230

Answers in %

1 0,43% 0,87% 1,30% 0,87% 1,74% 0,00% 0,00%2 3,48% 2,61% 8,70% 3,91% 6,09% 2,17% 1,74%3 5,65% 13,04% 23,48% 17,39% 20,00% 9,13% 17,83%4 40,87% 41,74% 40,43% 43,48% 37,83% 43,04% 32,17%5 49,57% 41,30% 25,65% 33,91% 33,48% 45,22% 46,96%

NA 0,00% 0,43% 0,43% 0,43% 0,87% 0,43% 1,30%Sum 100,00% 100,00% 100,00% 100,00% 100,00% 100,00% 100,00%

Q6 Q7 Q8 Q9 Q10

ANSWERS IN-MEMORY TECHNOLOGY

CLOUD COMPUTING

MOBILE COMPUTING

RISK MANAGE-

MENT

LIQUIDITY MAN-AGEMENT

REGULATORY REQUIREMENTS

1 0 7 22 10 5 6 5 1 42 10 29 44 29 33 35 º32 4 143 31 81 55 40 100 100 99 19 674 108 78 57 76 64 64 59 73 1165 78 32 50 73 15 12 22 127 24

NA 3 3 2 2 13 13 13 6 5Sum 230 230 230 230 230 230 230 230 230

Answers in % Reversed order

1 0,00% 3,04% 9,57% 4,35% 6,52% 5,22% 9,57% 0,43% 1,74%2 4,35% 12,61% 19,13% 12,61% 27,83% 27,83% 25,65% 1,74% 6,09%3 13,48% 35,22% 23,91% 17,39% 43,48% 43,48% 43,04% 8,26% 29,13%4 46,96% 33,91% 24,78% 33,04% 14,35% 15,22% 13,91% 31,74% 50,43%5 33,91% 13,91% 21,74% 31,74% 2,17% 2,61% 2,17% 55,22% 10,43%

NA 1,30% 1,30% 0,87% 0,87% 5,65% 5,65% 5,65% 2,61% 2,17%Sum 100,00% 100,00% 100,00% 100,00% 100,00% 100,00% 100,00% 100,00%

65


Q4 Q5

ANSWERS LCR AND NSFR

ECONOMIC CAPITAL

REGULATO-RY CAPITAL

LEVERAGE RATIO

VAR AND EXPECTED

SHORT-FALL

REAL-TIME ANALYTICS

ON-DEMAND DRILL-DOWN

FUNCTIONALITY

AGGREGATION AND COMPREHEN-

SIVENESS

SIMULATION AND STRESS

TESTING

1 15 10 11 11 13 11 2 0 52 28 22 20 28 12 23 9 4 123 95 63 60 74 56 51 44 27 384 52 93 82 79 88 79 110 114 965 27 31 41 24 49 64 63 79 77

NA 13 11 16 14 12 2 2 6 2Sum 230 230 230 230 230 230 230 230 230

Answers in %

1 6,52% 4,35% 4,78% 4,78% 5,65% 4,78% 0,87% 0,00% 2,17%2 12,17% 9,57% 8,70% 12,17% 5,22% 10,00% 3,91% 1,74% 5,22%3 41,30% 27,39% 26,09% 32,17% 24,35% 22,17% 19,13% 11,74% 16,52%4 22,61% 40,43% 35,65% 34,35% 38,26% 34,35% 47,83% 49,57% 41,74%5 11,74% 13,48% 17,83% 10,43% 21,30% 27,83% 27,39% 34,35% 33,48%

NA 5,65% 4,78% 6,96% 6,09% 5,22% 0,87% 0,87% 2,61% 0,87%Sum 100,00% 100,00% 100,00% 100,00% 100,00% 100,00% 100,00% 100,00% 100,00%

Question Q1 Q2_1 Q2_2 Q2_3 Q2_4 Q3_1 Q3_2 Q4_1 Q4_2 Q4_3 Q4_4 Q4_5

Voting factor 4,36 4,19 3,79 4,04 3,93 4,30 4,20 3,04 3,35 3,32 3,15 3,49

Question Q5_1 Q5_2 Q5_3 Q5_4 Q6 Q7_1 Q7_2 Q7_3 Q8_1 Q8_2 Q8_3 Q9 Q10

Voting factor 3,68 3,94 4,09 3,97 4,07 3,39 3,27 3,73 2,61 2,65 2,57 4,32 3,55

Aggregated results of the electronic survey

66

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