synpulse Rubrik | 1

The MagazineManagement know-how for practical use

Is Your Data on Your Balance Sheet?

How to Efficiently Implement Chatbots

Fraud in Private Banking – Are You Protected?

3 | 2017 int’l

synpulse | 3

«Intelligence is the ability to adapt to change.» Stephen Hawking

4 | Rubrik synpulse

Edito

rial

Are you also familiar with feelings of consternation when you learn from the daily news about the impacts of natural catastrophes that are becoming more frequent, intense, and devastating every year? When you come to know that they cause inconceivable human suffering and financial damage running into billions of dollars?

Only a couple of months ago, hurricane «Harvey» raged over the southern United States and was rated as the most fatal and expensive cyclone in American history so far. However just after that storm had passed, the next one called «Irma» was already on its way and was even more destructive than its precursor – much worse than «Katrina» in 2005 or «Andrew» in 1992.

It is all the more important to develop technology that can ensure fast and effective help in times of crisis. Particularly aid organizations rely on a possibility to filter relevant information out of a huge data pool quickly in order to initiate suitable emer-gency measures. In our series of interviews, called «From Outside In», Patrick Meier, who is an expert in the field of digital technology and co-founder of «We Robotics», presents a pioneering method for this kind of challenge. Taking advantage of drones and artificial intelligence, he and his team are developing strategies for a constructive and fast method of filtering and analyzing relevant information out of a plethora of data. Possible fields of application are disaster areas, developing countries, as well as nature conservation. In this context, I would also like to refer to the very inspiring interview with John Noel Victorino in edition 1/2017. He developed a unique mobile application for generating knowledge on how to behave during natural disasters. (You can find all published editions of «The Magazine» on our website www.synpulse.com.)

I am always enthusiastic when I get to know such unique personalities who invest lots of energy in mastering changes and who face future problems proactively. That is also our goal even though we deal with other topics, focusing on banks and insurance companies. We are likewise convinced that technological development – when used responsibly – can achieve many positive outcomes. Artificial intelligence, for example, is also part of our advisory business. Learn how the finance industry can take advantage of it as well in an article in this edition.

I wish you informative and inspiring reading.

Sincerely Christoph Nützenadel

synpulse

Editorial ................................................................................................................................................................................ 4

Digital Transformation

Partnering to Create a Better Journey for Customers ................................................................................................. 6 How to Efficiently Implement Chatbots ............................................................................................................................. 10

Digital Banking

Next Generation Community Bank ................................................................................................................................. 14 Is Your Data on Your Balance Sheet? ............................................................................................................................... 18

From Outside In

Interview with Patrick Meier: Robotics Technology for Humanitarian Use .................................................................................................................. 22

Regulatory & Compliance

Fraud in Private Banking – Are You Protected? ............................................................................................................. 26 IFRS 9 – A Paradigm Change in Financial Reporting? .................................................................................................. 30 CRS – Choosing the Correct Reporting Model Is Half the Job Done ......................................................................... 34

Operational Excellence

Scaling the Wealth – Consolidation in the UK Wealth Management Industry ........................................................ 38

Masthead .............................................................................................................................................................................. 42

Table of contents | 5

synpulse6 | Digital Transformation

Partnering to Create a Better Journey for Customers

The life insurance industry faces challenges gaining and retaining customers. The traditional approach continues to underperform modern proceedings such as a data-driven under-writing. To stay competitive, insurers have to adopt a digital ecosystem with other technology providers.

Authors: Christian Seidel | Sheena Strawter-Anthony

Life insurance is out of touch with young families, one of the core customer segments. Analyzing the typical customer journey of traditional life insurers quickly results in the conclusion that there are many built-in sales barriers. In fact, the product is not easily accessible for many and straight-through-processing is nonexistent for over 80% of the appli-cants. These observations are also valid for the servicing and administration of existing customers. It is a myth that people who do not own insurance do not want it. According to the research organization «LIMRA», 19 million insurance shoppers got stuck because they did not know what or how much coverage to buy.

New players like «Haven Life» and «Ladder» in the US concen-trate on the engagement and distribution of new customers. A data-driven underwriting approach advertises quick and simple application processes at competitive rates. Traditional players must rethink their positioning, because significant transformations are predicted in most areas of the industry’s value chain. Technology partners offer new opportunities but if insurers do not catch up with the present, tech-savvy and disruptive players, they will fall behind; thus they disaggre-gate the insurance value chain in the future and change the nature of the insurance business to a digital ecosystem.

Requirements for life insurersProduct development requires the specialization of product features and the ability to customize the products quickly to fit the channels provided through the digital ecosystem. Here, customers expect to spend less time researching products and easily understand features, terms, and conditions. Aggregators and technology providers disconnect the distribution of personal policies and the ownership of customer relationships from insurers. Customer loyalty decreases as aggregators cre-ate distance between the individuals and their insurer. Com-petitive advantages offset existing retail channels (e. g. agent force, brand). As health (risk) awareness rises, individual risks are increasingly standardized and commoditized. The impor-tance of actuarial and underwriting capabilities grows as other parts of the value chain disaggregate. Insurers’ margins on personal and small commercial products are decreasing.

A larger proportion of investment risks are transferred outside the insurance companies as more alternative providers of capital (e. g. hedge funds) offer cost-effective options. Growth of insurers is less constrained by their access to risk capital. Increased underwriting capacity, transfer of catastrophic risks and commoditization of risks may lead to a decreased impact of insurance cycles.

synpulse Digital Transformation | 7

Change has yet to comeThe above results in insurance companies facing challenges on several fronts. Insurers’ legacy IT systems are complex, which limits their agility. A bias towards largely intermediated distribution and the technical nature of products hinder a shift towards greater consumer orientation. Complex insurers, often siloed by branches or lines of business and long-term view, tend to have a limited focus on innovation. In many countries, the economic environment creates significant

pressure in terms of investment capability, increasing the short-term focus of insurance companies. Facing these challenges, insurers need to focus on the following:

Consumer centricity: Insurers will need to tailor their offers and services to the real needs of their customers. For many, this will entail a radical shift in their core processes, such as new product development, customer contact and claims process design.

1: Strategic Approach for Engagement and Distribution of Customers

Source: Synpulse

R&D productmanufacturing Distribution Underwriting Risk & investment

management

Customer heterogeneity Data sources Innovation in analyti cal

tools

Utilization of data analytics

Wearable devices integration

Portfolio creation Product customization

Increasing competition in underwriting process efficiency

Broad source of information and data

Device-integrated UW process

Rule-based UW Point-of-sale UW Effective case management

Increasing demand for transparency

Emerging digital policies purchase platforms

Intensive competitions due to information flow

Mobile platform Online aggregator Online purchase platform Social media Advice model to self-

direct model

Customers seek honest and transparent advise

Robo-advising Data predictive analytics External solutions

5 5 53 3 3 32 21 1 1 1

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3

4

5

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Dri

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chan

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bser

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Online distribution

Wearables

Predictive analytics/data

Robo-advisors

Machine learning & cognitive systems

synpulse8 | Digital Transformation

Cutting across silos: The digital paradigm requires that silos between branches and functions are broken down.

Partnerships: Insurers need to sign up suitable partners to develop more immersive ecosystem offerings.

IT evolution & flexibility: Digital technology requires (front-end) IT systems to operate on a different level. Consumer data must be easily accessible; operations need to happen in real time. New alternative distribution partners need to be on-boarded in no time. Consequently, IT systems have to find a way to manage the evolution of insurers’ core sys-tems at a measured pace while enabling rapid absorption of technological innovation. In short, they need to manage «two-speed IT».

Innovation: Adapting to the digital world requires sound knowledge of the technology available; ability to develop, test and pilot at the right pace; readiness to fail in an entrepreneurial spirit; and capacity to do all that without jeopardizing the core business. Insurers will also have to scan the horizon for new, game-changing technology that may be too far ahead to commercialize now, but could have a significant long-term impact on the industry.

Data analytics: New capabilities offered by big data tech-nology need to be embedded within insurance and need to support most of the underlying changes.

Unleashing the potentialAn ecosystem can help life insurers become more customer centric, data driven, innovative and efficient. Ecosystems are best achieved by assessing the value chain and identifying partners for synergies along the customer life-cycle and cost effectiveness. Potential partners, who complement or substi-tute an insurer in a value chain activity directly or indirectly, are identified by mapping core competencies required in a complete customer lifecycle and servicing framework. The thought process behind structuring the partnership portfolio begins with core competency mapping and matching against the customer lifecycle and servicing framework. From there, partners are assessed for their readiness to syner-gize with the insurer’s requirements and cope with regulation, process and service quality boundaries.

Most common are ecosystem partners who support the need and research stages of the lifecycle. Aggregators, concierge

services, and marketing profiling, all these can be found frequently on the market and strive to engage closer with potential customers. For life insurers, it is important to select the right partner according to their own attribution. With respect to aggregators, for example, these shall include:

Reaching the mass versus segments: Many aggregators and other ecosystem partners may be segmented into mass players or players who personalize the offering to a specific market. Therefore it is important for the life insurer to choose between commoditization or individual-ism in product design and distribution.

Showing collaborative capabilities: Successful lead conversion can only happen if both players, the insurer and the aggregator, can integrate to the extent that the critical mass is reached. Web traffic on the aggregator’s website provides an initial indication. However, the product mix of the insurers has to correspond to the offering of the aggregator to convert the web traffic into leads. Multi-line aggregators might be a better fit for multi-line insurers.

Covering the value chain: It is also important to assess how far the aggregator covers the value chain. Nowadays aggregators cover lead generation to underwriting and policy servicing. On the one hand, there might be a busi-ness case for life insurers to gain savings, because the aggregator covers the operational aspects at a lower cost. On the other hand, the life insurer’s processes have to be mature to allow for such deep integrations.

Involving aggregators and other potential ecosystem partners into the business model generates value for all three – the customer, insurer, and partner – but only if these synergies can be unleashed.

synpulse

Authors

Digital Transformation | 9

Christian SeidelAssociate Partner (Synpulse USA)christian.seidel@synpulse.com

Sheena Strawter-AnthonySenior Consultant (Synpulse USA)sheena.strawter-anthony@synpulse.com

New ecosystem business models

New business models have emerged and now pose potential competition to incumbents.

Aggregators: Online aggregators that allow customers to compare prices and purchase insurance products online may displace traditional distribution channels as customer preferences change and more insurance products are commod-itized (e.g. UK P&C market).

Telematics: Use of existing and new data. In underwriting, medical assessment at point of sales as well as flexible client analytics are made possible. In pricing, dynamic pricing models such as «Pay-As-You-Live», flexible yearly premium, and product adjustments are offered. Sales and distribution develop into new, electronic distribution, multi-channel marketing, and a holistic, customer-centric approach. Portfolio management now allows increased client touch points and target-group-oriented marketing for e. g. 50+. Sources may include electronic

health and prescription records, credit history, and behavioral data.

Sharing economy: As sharing economies emerge from «Pay-As-You-Go» rentals to shared vehicles and houses, the concept of ownership may radically change, challenging traditional insurance models developed based on one-to-one ownership structure.

Securitization: Insurance-linked securities such as catastrophe bonds are introducing new pools of capital providing fully collateralized coverage to insurers, outside traditional re-insurance and insurance pools.

Entry of tech players: Technology providers with brand recog-nition and trust may enter the insurance distribution market, leveraging their extensive data and distribution capability. Largest technology companies acquire InsurTech startups, e.g. Google acquired the UK e-aggregator «BeatThatQuote», who charged insurers up to USD 54 per click.

synpulse10 | Digital Transformation

How to Efficiently Implement Chatbots

Chat is becoming more and more relevant as an interaction channel between customers and businesses. Recent advances in artificial intelligence enable the development of efficient chatbots that understand natural language. The financial services industry is becoming increasingly aware of the emerging opportunities.

Authors: Weili Gao | Karim Attia

Chatbots are computer programs that can chat with people automatically, e.g. via Facebook Messenger. This means that customers can interact with a company via chatbots just as they would with a human customer service representative. Chatbots have debuted in 2016 for business use, and we expect them to become the primary way customers engage with companies within the next few years.

Benefits of chatbotsChatbots offer many benefits that enable financial services providers to fundamentally reshape and improve their customer interaction. Chatbots are much easier to use than customer portals or mobile apps as the customer doesn’t need to search for the right webpage or go through complex menus to find relevant information or to place a request. Instead, customers can just start chatting with their bank or insurer. It will automatically navigate them through the correct process – just as if they were talking to an insurance broker, financial advisor, or customer service employee, but with 24/7 availability and no waiting time.

Furthermore, chatbots can serve as a single point of contact. This means that customers are able to access all the available services of a financial service provider as well as various third-

party services via a single messaging app. Chatbots allow banks and insurers to automate most of their customer inter-action, resulting in a significant reduction of labor costs and processing time for customer requests. Additionally, a chatbot is easy to scale as it can communicate with thousands of customers on different messaging platforms at the same time. Finally, it is possible to program efficient chatbots with relatively low cost and time investment due to the large number of available chatbot development platforms. By using pre-trained artificial intelligence (AI) models from providers such as Microsoft, IBM, Google, Amazon or Facebook as a basis, it is possible to reduce the amount of effort required to train a chatbot significantly.

How modern chatbots workAs soon as a chatbot receives a message from a user, it has to identify the intent of the user’s request. It then guides the user through the relevant business process by providing him with information and determining required parameters by using so-called entities.

Thus, when developing a chatbot, it is necessary to first specify the intents and entities that the underlying AI should be able to identify when receiving a request from a client. With the

synpulse Digital Transformation | 11

help of a few sample user inputs and the machine learning approach, the chatbot is then able to link previously unknown user input sentences to the correct intents and entities. Comparable to a child who naturally makes many mistakes when it first starts to learn how to speak, a chatbot initially makes many mistakes when processing natural language. We can improve the accuracy of intent and entity identifica-tion by training the chatbot with additional annotated user inputs. This training effort can be reduced significantly by using a pre-trained «natural language processing model» (NLP model) from AI-as-a-service providers.

How to avoid pitfalls when introducing chatbots Financial services providers are still hesitant about investing too heavily into chatbot technology. Before committing more resources, they first want to assess the reaction of their customers. They typically start experimenting with chatbots by initially automating only a few selected processes involving customer interaction. Accordingly, the customers of the finan-cial services providers need to be informed that they will only be able to access a very limited number of services when using the chatbot. The answer to any customer request that exceeds the abilities of the chatbot is a response such as «Sorry, I could not understand you». Thus, there are two problems arising from this proceeding:

Chatbots with limited scope will only gain little acceptance among customers due to the poor user experience. Therefore customers must constantly make the mental effort to consider how to phrase their messages in a way that the chatbot will understand them.

These chatbots are deployed to work without any human supervision. Hence, they need to be 100% accurate in processing user input to avoid errors in the business process. However, attaining 100% accuracy often requires a lot of training for the chatbot, and in some cases it might even be impossible to achieve that goal with the current state of technology.

Gradual automationWe therefore suggest a different approach: Human agents work closely together with chatbots to achieve an optimal customer experience ( 1):

1. First, introduce chat (without chatbot) as a new interaction channel through which customers can access the full array of available services. At this stage, incoming requests are still processed by human agents, typically in traditional customer service centers.

1: Gradual Automation of Customer Interactions via Chatbots

Source: Synpulse

Introduce chat asnew interaction channel

Deploy chatbotinto chat channel

Continuous training of chatbot From chat to voice

Immediate benefits since automation and training starts right away

Chatbot hands over unknown requests to humans agents

Customer can access all available services via chat immediately

Requests sent via chat are processed by human agents

Stage 1: Stage 2: Stage 3: Stage 4:

Number of hand-overs to human agents is reduced continuously as the abilities of the chatbot improve

Extension to voice-based interaction

Integration into virtual assistants and smart home devices

Send responses based on customer analytics & sentiment analysis

Complete automation of customer interaction

No more need for expensive call centers or customer por-tals and apps

Benefit: A customer can always access the full array of services as if talking to a human agent

Final vision

synpulse12 | Digital Transformation

2. Next, a basic chatbot is deployed into the chat channel established in the previous step. This chatbot will only be able to handle simple requests initially. Whenever it receives a request it cannot process, it automatically hands over control of the chat to a human agent who will reply to the customer.

3. Use the incoming customer requests and the corres-ponding responses and decisions of the human agents as training data to improve the chatbot continuously. With time and training, the chatbot can handle more and more requests autonomously, i.e. without human intervention.

4. Expand the chatbot with further capabilities, such as

voice-based interaction, or modify responses based on customer analytics and sentiment analysis.

Handover between chatbots and human agentsAn important requirement of the gradual automation approach is the smooth transition between chatbots and human agents. Unless general artificial intelligence steps out of the realm of science fiction, there will always be times where the chatbot needs to reach out to a human being.

Whenever the chatbot is not sufficiently confident about the processing of user input, it sends its proposed response to a human agent ( 2). The agent then decides whether to directly forward the chatbot’s response to the customer, or to modify the response first before sending a reply. The agent’s decision is then used to train the chatbot for similar future requests.

Virtual assistantsIn 2015, Facebook launched a virtual assistant called «M» on their «Messenger Platform» that adopts a chatbot-human hybrid approach to process user requests, just like the concept we suggested above. In contrast to completely AI-based virtual assistants like «Siri» or «Alexa», the responses generated by M are always sent to human agents initially. These agents then decide whether to directly forward M’s responses to the users or whether to intervene before replying.For example, users can make a reservation at a restaurant via M. The human agents simply call the restaurant for the customers. The users of M do not know if they are currently chatting with a chatbot or a human agent. Facebook records all interactions between the customers and M and uses this data to further improve the NLP capabilities of M’s AI.

2: Dynamic Handover from the Chatbot to a Human Agent

Source: Synpulse

Incoming customer request

Send automatically generated response

Chatbot > 99% confidence

Chatbot < 99% confidence

Hi, I would like to buy an insurance.

Send suggested response to human agent

Hi Tim, thank you for your interest! Which type

of cover do you need?

How the interface of a human agentcould look like after a handover

Intent: Buy insurance

Homeowners insurance

Private liability insurance

Vehicle insurance

Sendresponse

Modifyresponse

synpulse Digital Transformation | 13

Authors

Current virtual assistants like Siri or Alexa cannot communicate with restaurants or insurance companies to make a reservation or to purchase an insurance product on behalf of customers. Imagine they could do this by forwarding requests to the businesses in natural language. Which restaurant would the virtual assistant select to make a dinner reservation? Which insurance company would it choose to purchase travel insurance? Certainly, not the one with which it cannot communicate.

Conclusion and outlook Chatbots are not just a current hype but will become an important part of future business models. They enable businesses to offer their customers a new type of interaction to improve sales performance and to reduce costs. Customers

will become used to communicating with companies via messaging apps, virtual assistants, and smart home devices. We expect that companies will even start designing products specifically tailored to chatbots.

Despite their many benefits, chatbots still require a well-thought-out strategic initiative so that they can be successfully deployed in customer interaction. Devising such an initiative requires in-depth knowledge of chatbots as well as detailed industry-specific know-how.

Weili GaoConsultant (Synpulse Switzerland)weili.gao@synpulse.com

Karim AttiaConsultant (Synpulse Switzerland)karim.attia@synpulse.com

synpulse14 | Digital Banking

Current environmentTwo essential factors for keeping up with today’s competitive banking industry are technology adoption and digitization. New technology platforms like «cloud computing» and «robo-advisors» present countless choices for executives that are now required to understand bank customers as well as how technology enhances their customer experience. Traditional banking services augmented with strategic technologies enable community banks to compete with large e-commerce and national banks while still embracing a client-centric operating model.

The most important attributes for community banks are summarized in the classical «SWOT» analysis (strengths, weaknesses, opportunities, threats) in 1.

Target landscapeFace-to-face advisory will still play a role for community banks but clients’ expectations will shift towards a digital, self-managed banking experience. The evolution of traditional

bank services means that future demand for client service representatives will decrease. Also the remaining advisors will assume new technology-augmented roles that will involve consulting on estate and wealth planning, insurance coverage, philanthropy, and tax planning. Simple tasks such as account and checking management will be left for machines to manage.

The following five strategic initiatives provide areas where community banks heading into the future could leverage technology to assist with digital demands ( 2).

1. Tapering of process inefficiencies through Robotic Process Automation; main goal: cost reductionIntroducing Robotic Process Automation (RPA) solutions can reduce operational errors and increase process efficiency by providing rule-based systems that detect and correct errors in real-time. RPA technology provides comprehensive support for time-consuming manual tasks, such as «Know Your Customer» (KYC) data collection and loan submission. As a

Next Generation Community Bank

Personal customer relationships play a vital role for the success of community banks1. But new players with extensive digital capabilities threaten these personal service-oriented banks. In order to stay competitive, community banks have to consider taking advantage of digital strategies that enhance their customer relationship management.

Authors: Mathias Hausherr | Pallav Kapur

1 A community bank is an independent depository institution which is owned and operated by the local working community. It typically provides traditional banking services.

synpulse Digital Banking | 15

first step, in order to understand where there is potential to implement RPA technology, bank executives need to analyze and map their complete existing process landscape with regard to products and business units. After a feasibility assessment, robots can be programmed and embedded into the existing operating model, resulting in reduced manual labor, freeing up resources for more value-added activities. For example, robots replace database administrators to e nsure complete and accurate data models, which allow adminis-trators the time to develop analytical tools and to better understand client behavior.

2. Enhance client interaction through data capitalization; main goal: increase client experience & profitBy leveraging community presence and utilizing affordable technology to improve customer insights, community banks can secure their place for a vital role in future economic devel-opment. Community banks must focus on customer retention with enhanced customer insights for sustainable business. With the appropriate toolset (e.g. data insight platforms like «Squirro»), community banks can better understand client needs and proactively provide solutions or products to meet their demands. Besides assisting with cross-selling oppor-

tunities, customer insights solutions enhance the already individualized role of community banks. Customer insight technologies pull information from both external and internal sources to generate a 360 degree, comprehensive representa-tion of the clients’ circumstances and anticipate their next best action. Community banks could use customer insights to focus on generational wealth transfer, asset retention; and additionally, as a security layer for local loan decisions.

Properly applied, data analytic tools will reduce time consuming and labor-intensive processes in the community bank and allow representatives to better serve the clients. High employee tenure and lower labor cost provide a unique opportunity for community banks to invest in educating and retooling their current workforce. With an enhanced skillset, representatives will build upon their already customer-oriented interactions and provide better understanding and structuring of services for their target segments.

3. Automatization of risk & compliance rules and reporting requirements; main goal: cost reduction Currently available and used by large banks, real time processing and reporting of multidimensional and complex

1: Important Attributes for Community Banks Shown in the Classical «SWOT» Analysis

Source: Synpulse

Vicinity and trustworthiness Good standing in the community (reputa-

tion, establishment, personal networks, social responsibility )

Proficient local market knowledge Local decision-making capabilities

Insufficient 24/7 (digital) delivery of banking services (poor user experience)

Bank processes are not customer-led Brick & mortar distribution limits market expansion Tech-savvy executives Legacy IT seen as support and not as «business

driver gap»

Emergence of non-traditional bank market players Switching banks is easier than ever before Further increasing regulatory requirements drive

costs and lower margins Challenged non-distinctive banking models

leading to the overall reduction of workforce and attractiveness for talents to join the community banking industry

Technology enabled products leading to new markets

Generational transfer of wealth (educational opportunities for saving and spending)

Regulatory authorities evolve and support compliance & reporting automation. Fintechs seek for white labeling of their products rather than competing

Strengths Weaknesses

ThreatsOpportunities

synpulse16 | Digital Banking

data provide advance governance and risk mitigation capabilities. As regulators apply more compliance regulations to banks, data management solutions will help community banks to apply changes quickly in order to control models, avoid late or incorrect reporting, and better capitalize on economies of scale for regulatory compliance efforts. Specific software solutions, such as «Qumram», allow banks to monitor digital client interaction in real time continuously to identify new errors, abuse, fraud and non-compliance.

4. Cloud-based workflow solutions to enhance the regional market; main goal: business volume increaseAs clients become more digitally adept, extensive networks of local branches will become obsolete and the focus will shift to enhanced technology capabilities. Bank representatives will be required to support and utilize technology among their day-to-day duties. Work-flow solutions create order and effi-ciency for community banks. As the full customer lifecycle will be digital, work flow solutions delegate tasks to the appropriate bank employee to ensure seamless and prompt response time

for clients. Workflow solutions also support the expected digi-tal customer experience, for example, by assuring faster loan origination due to decreased manual processing while reducing fraud and compliance risk with detailed audit logs.

5. Holistic, family office like «Advisor of Trust Approach»; main goal: a larger percentage of individuals’ portfoliosLocal banks should become a family office like a one-stop-shop agency that provides services such as education, investment, tax and philanthropic planning, as well as lifestyle management. As an example, the local advisor of a trust consults a family on better health insurance conditions by making use of wearables, refer them to nutrition coaches and so forth.

Once the family has been coached and accompanied for a more financially optimized «family life cycle», the risk of losing the younger generation that inherits current wealth will also shrink. Currently there is a high chance that subsequent gen-erations will remove assets from community banks in exchange

2: Five Initiatives of Using Technology in Community Banks for Digital Demands

Source: Synpulse

Family-oriented approach

Community bank

RPA Workflow management

Data insights

Cloud-based solutions

synpulse Digital Banking | 17

Authors

Mathias HausherrAssociate Partner and Managing Director (Synpulse USA)mathias.hausherr@synpulse.com

Pallav KapurManager (Synpulse USA)pallav.kapur@synpulse.com

for a larger bank with a more digital and user-friendly experi-ence. Community banks pride themselves on their strength in person services, community presence and customer loyalty. To succeed in the increasingly competitive digital banking era, community banks must develop loyal relationships with not only clients but also third-party vendors. Third-party vendors allow community banks to leverage cutting -edge technology without building out complex IT infra structure. This allows community banks to benefit from the power to provide a digital experience like a large institution, with a state-of-the-art IT service environment at a fraction of the cost.

ConclusionPlain vanilla banking services such as loans, checking accounts, and credit cards could remain with community banks but it is vital that these services are augmented with innovative digital solutions to meet customer demand. Alternative and larger competitors will offer them faster, cheaper, and more integrated with existing products. To keep pace in a rapidly evolving market, the operating model of community banks must evolve.

A use case

Cost reduction and geographic expansionIssuing and servicing small and medium loans within a US south-west community bank was reaching a point of unprof-itability. Wishing to provide smaller loans in a faster, more mobile and digital manner to local business owners, the bank began exploring possibilities that would help reduce cumber-some manual processes, perform a holistic risk assessment and expand their geographical footprint.

The bank’s legacy loan generation software required business owners personally attend loan consultations, complete appli-cations, and closing activities with a loan officer at one of their branches.

Synpulse’s major contributions to tackle the challenge!The bank approchaed Synpulse to support their decision pro-cess and we created, modeled and validated a benchmark framework and assessment for loan origination processes. Our benchmark framework establishes costs associated with a bank's current loan generation process and identifies areas of gained efficiency associated with the to-be process.

A digital loan platform promotes efficiency among employees who will service more loans and generate more profit. Addition-ally, the solution will support a geographic friendly online inter-face, ultimately reducing or eliminating the need for business owners to visit one of the few brick-and-mortar locations.

The role of Synpulse includes process analysis and coaching for management and employees on the benefits of the new digital loan solution.

synpulse18 | Digital Banking

Is Your Data on Your Balance Sheet?

Nowadays hardly anyone doubts the strategic importance of data, yet the statement that it’s a «valuable asset» sounds too figurative unless true value is assigned to it and this asset is managed as such. Which are the opportunities and implications of this idea for the private banking and wealth management industry?

Author: Vladimir Dimitroff

synpulse Digital Banking | 19

We live in the age of big data, advanced analytics, and artificial intelligence. It is widely recognized that the availability of diverse, detailed and wide-reaching data, and the capabilities to utilize it in decision-making provide a distinct competitive edge to any business. Advances in data analytics are embraced and utilized by the private wealth (private banking and wealth management) industry in a fragmented manner and the sector lags behind retail banking or insurance, not to mention «digitally native» industries such as e-commerce or telecoms. A coherent data strategy and a transformation to a data-driven organization, therefore become significant competitive opportunities for a private wealth organization, and in some cases – even a survival imperative. The roadmap for such transformation inevitably includes an evolving cross- functional maturity view, and enabling enterprise-wide changes in operating model and culture.

The data-driven organizationWhat are the characteristics that qualify a business as «data-driven»? Having and using data is apparently not enough, as we all have and use this commodity just like we use electricity – without even thinking about it. A true data-driven organization can be defined by its commitment to data as a central component of long-term business strategy. As a result of such commitment, such companies have

a dedicated data strategy with a clear vision about data ownership and management, and a roadmap for growing both the data and related capabilities,

a governance structure and operational plans for continu-ing improvements in data-dependent and data-generating areas of the business,

a business case and corresponding investment commit-ments for the fulfilment of the strategic vision, and last – but not least –

a financial view of «all things data» where the business benefits of owning and processing data, as well as the associated costs, are represented with clear monetary values and drive respective budgets and performance metrics.

As we have discussed in other papers, the evolution of data-driven organizations is a journey with distinct stages of matu-rity and every company is at some point of that journey. The financial criterion above is a good indicator of maturity, as it confirms the other criteria: It takes commitment to develop a data strategy and a pragmatically planning mindset to grasp the need for a financial approach. Only the more mature businesses would have this in place and would use it to drive improvements.

What is the current state of the industry in this respect? Once the hype about big data fades away and it becomes business-as-usual, it is easier to separate lip service from genuine actions. Have you read or heard the statement «Our data is one of our most valuable assets»? According to a recent study by Ernst & Young (EY), out of 150 financial services companies 83% said that data is their most strategic asset. A similar num-ber (84%) also said data is a source of competitive advantage. Yet almost half of them – 47% – have no idea about the real value of their data. And about a third – 31% – admit that they don’t have the needed capabilities to extract value from their data1.

83% of financial services companies declare that data is their most stra-

tegic asset, but 47% do not know its value and 31% are poorly prepared to

extract value from it.

This was declared by insurance, banking and a broader range of financial services organizations. In private wealth, the pic-ture is even less encouraging, due to historic protective atti-tudes towards high net worth client information and overall more conservative business practices. The changing nature of wealth management, however – with market pressures like regulation and fintech disruptors – already obliges sector play-ers to re-examine their data-driven maturity.

Reasons to know the value of your dataThe capabilities to acquire, organize, protect, process, and profit from data require considerable investments, both capi-

1 Source: EY – «The Science of Winning in Financial Services»

synpulse

tal and operational. It is unthinkable to commit to such invest-ments without an accurate appraisal of the asset you are try-ing to manage. Assigning financial attributes (including a monetary value) to data thus becomes an imperative for the data-driven organization. Knowing historic, current and pro-jected data value can be directly useful in certain scenarios:

Building a business case to justify, as mentioned, invest-ment in data management infrastructure, technical capa-bilities and human skills

Innovating for data-based new product and service offer-ings, treating data as a new revenue resource

Adding (significantly) to the value of the entire company in M&A cases; this is currently very frequent, particularly in the UK, where the fragmented wealth management industry is undergoing rapid consolidation

From pricing in M&A situations to developing innovative products and

services, knowing your data value has become an imperative.

A number of smaller and subordinated reasons add to the picture and help justify the effort to assign value to your data – from acquisition (at a cost) of extra data from public and third party sources, to the costs of compliance with data protection regulations. But where do we start – exactly to approach the valuation of data?

Approaches in the valuation of data as an assetLike most intangible assets (patents, trademarks, domain names or software), datasets and database contents can be valued in one (or more) of the three fundamental appraisal methods:

Cost-based

Income-based

Market-based

The cost-based method, as the name suggests, accounts for the costs incurred in acquiring the data and the historic costs

of its maintenance to its present state. This has well docu-mented inputs and can be very accurate, however it is poorly (if at all) related to the potential for extracting value from the asset. Data can be precious as well as worthless, and costs do not indicate those possibilities.

The income-based method, on the other hand, focuses on the revenue opportunities from exploiting the data and thus is much better for pricing if data is to be sold as such, or if it is an asset when the entire business is sold or merged. This can be done for current income levels, or at net present value of future projections, making the valuation models predictive. The result, compared to (separately calculated) costs can be disappointing or lucrative, which justifies attempting a hybrid approach: net present value of projected revenues, minus acquisition and maintenance costs. Financial experts debate many details of such models, but they are closest to an accu-rate, decision-supporting idea of data value.

The market-based approach can often be brutal, but it most objectively reflects the fundamental principle of Adam Smith’s «invisible hand». Markets account for (and discount for) both incurred costs and, especially, earning potentials. It even con-siders, albeit not too transparently, the behavioural psychol-ogy of buying and selling parties that reflects their own per-ceptions of value.

The right price of anything is as much as those who need it are prepared to

pay for it.

Market-based valuations are reliable when there are signifi-cant transaction flows to observe and align with. When considering that data-related deals are a smaller number, it is inappropriate to talk about «market price» as any single precedent risks being an anomaly.

Once we mention hybrid approaches, market information can be included in an income-minus-cost model as an adjustment, a weight factor to make the internal valuation more relevant to other parties.

Steps to leverage the potential of dataData is undoubtedly the most strategic asset, deserves to be treated as such, and should have its place in a firm’s financials

20 | Digital Banking

synpulse

Author

Vladimir DimitroffPrincipal (Synpulse United Kingdom)vladimir.dimitroff@synpulse.com

Digital Banking | 21

including the balance sheet. To reach such a level of maturity, private wealth companies need to

assess their current state and draw a roadmap to their envisioned capability level,

commit to a data-driven corporate strategy and to a func-tional data strategy aligned with that vision,

allocate resources and responsibilities to manage every phase and step in the roadmap,

make initial steps towards a financial view of their data, estimate a value and, while continuing to improve its accuracy, start using the value in business cases and critical decisions.

synpulse22 | From Outside In

Robotics Technology for Humanitarian Use

The American-Swiss nongovernmental organization «WeRobotics» uses unmanned aircraft for social and ecological purposes in developing and disaster-prone countries. Patrick Meier, the co-founder and expert in the field of digital technology for humanitarian issues, explains how robotics technology can be used for development and emergency aid.

Interview with Dr. Patrick Meier

synpulse From Outside In | 23

Drones are normally associated with warfare. With «WeRobotics» you demonstrate that drones and other robotic vehicles can be used for humanitarian and environmental purposes. How can people in need and the environment benefit from that?The science of artificial intelligence (AI) and robotics is quite distinct in the field of emerging technologies. Before the rise of AI and robotics, technology was manually controlled. Now, it can be operated on an autonomous or semi- autonomous basis and programmed to collect data or deliver cargo. As it is not manually intensive, it is safer, cheaper, and quicker than previous technology. In a humanitarian context, data can be collected with higher resolution and also in realtime. Life-saving cargo can also be delivered more quickly using robotics.

How did you come up with the idea of founding WeRobotics and linking robotics usage to humanitarian aid? I have been exploring drones and robotics for the past ten years. For me personally, the catalyst experience was the devastating earthquake in Nepal in the spring of 2015. I was asked by the United Nations to help coordinate the use of drones in response to the catastrophe. As a result, I had to coordinate several teams, including startups from Silicon Valley who had never worked in Nepal or in a developing country. This turned out to be a complete disaster. I witnessed firsthand how important it is that we localize robotics solu-tions and train local pilots, who already know the language, country, and customs, and who won’t leave once the media coverage subsides.

One current project of WeRobotics tackles the spread of the Zika virus. Could you tell us a bit more about this? What are the specific challenges regarding the use of unmanned aerial vehicles (UAVs)? A number of studies have been published over the years on how to reduce mosquito populations. One of the most inter-esting insights to come out of these studies is a new technique that focuses on sterilizing male mosquitoes and releasing them to reduce the overall mosquito population. This often proves to be a better solution than using chemicals, which have an environmental and public-health impact. So, to employ this technique, mosquitoes are put into boxes with a special release mechanism and are then transported by a car or truck into the relevant areas. Although this ground-release approach is quite effective, you need to consider that you must have functioning roads. In developing countries roads

are potentially not in a good condition and may be impassable during the rainy season. Unfortunately, mosquitoes multiply during the rainy season. Also, you have to take into account that communities might not live next to a road. So, we are exploring the use of drones to complement the release of mosquitoes. This is not trivial, as you have to develop and engineer a semi-autonomous release mechanism that can be carried by a drone. We plan to test this in Peru and hope that it will turn out to be effective.

Robotics technology not only encompasses aerial vehicles but also terrestrial and maritime vehicles. How advanced is robotics technology in each area and how can robotic vehicles be employed to detect environmental problems?Marine robotics is ahead of terrestrial robotics. So far, terrestrial robotics has primarily been used for search, rescue and demining. Aerial and marine robotics can be used, for example, for pollution detection, counting the population of sea life, or monitoring algae blooms. In Tanzania we are currently doing coastal monitoring. One of our partners in Canada is developing a terrestrial robot to pick up plastic in polluted areas. We hope to secure funding so we can leverage this solution for use in polluted lakes in Nepal.

How strongly do you depend on the cooperation with local governments?Many of our projects include government bodies as formal partners. In Tanzania, for example, our Flying Lab was asked by the Ministry of Interior to carry out aerial surveys of the city of Bukoba following the earthquake there in 2016. The Ministry wanted to have a better assessment of the recovery and reconstruction. All our projects also require formal permission from the respective Ministries of Aviation, so we also work closely with these bodies.

You call your operating places all over the world (e.g. Tanzania, Nepal or Peru) «Flying Labs». Your work is based on partner-ships with local communities, not-for-profit groups, universi-ties and governments. How do you manage to work with these local communities and to gain their trust, especially if they have an indigenous lifestyle?In order to do projects in a local community, we first need a formal permission. Subsequently our local team, who runs our Flying Lab, introduces itself to the local communities and builds long-term relationships. The local communities also become actively involved in the project and help us to con-sider domestic rules. For example, there might be areas that

synpulse24 | From Outside In

are sensitive to fly over, such as cemeteries, so these need to be avoided.

One of your goals is to incentivize local entrepreneurship. Have you already experienced cases where local partners have founded other Flying Labs in their region?WeRobotics was founded in 2015 and we launched our first Flying Lab in 2016. Since then, two of our labs (in Nepal and Tanzania) have received requests from neighboring countries to establish labs there, which we’re very excited about. Earlier this year, we also provided business incubation training in Nepal, focused on robotics or «drones as a service», which means that drones can be used to generate maps, 3D models, indexes, aerial imagery, and provide many other services. During that process we also helped to incubate three local Nepali startup companies that offer drones as a service. We’re doing the same in Tanzania this fall.

The installation of Flying Labs unfolds along a four-phased framework. Could you specify these phases? The first phase is the scoping phase where we identify countries with pressing challenges. The next step for us is to further distinguish which countries are local champions keen on exploring technologies. Then we also check if robotics can be a solution for the problems, and if so, which type of robotics can be considered for use. The second phase is building local capacity. Here we provide training and technology transfers to our Flying Labs staff and support their first projects. The third phase comprises remote support. Here, projects run on their own. The Flying Labs rely on other labs and learning networks. The fourth and final phase encompasses incubation. This means, that the Flying Labs should create local markets, local ecosystems, and jobs by incubating local businesses.

Can you tell us about one specific project in which you pioneered humanitarian aid and achieved fast success and improved the lives of people in need?I experienced this a long time ago in Haiti during the devastating earthquake of 2010. Here, crowd sourcing and disaster mapping were used for the first time. Digital volun-teers began extracting various data sources like social media and text messages to detect areas of damage and need. Haitians living abroad assisted with translating the messages – so we had digital v olunteers who cooperated in a global initiative. This was the first major milestone for digital humanitarianism.

Besides your headquarters in Washington, D.C. WeRobotics has opened a second office in Geneva, Switzerland, this year. What are your business targets in Europe?Three of the four co-founders of WeRobotics, including myself, are Swiss (Sonja Betschart and Adam Klaptocz are based in Switzerland, Andrew Schroeder and I are based in the USA). So opening an office in Switzerland was a natural next step. We selected Geneva for strategic reasons: the United Nations and many other international organizations are also based in Geneva. Furthermore there are leading universities and Swiss companies with whom we can build partnerships for fundraising. It is our goal to gain more visibility in Europe, develop our business and partnerships and diversify our funding base.

How does WeRobotics fund itself? The first pillar of funding is derived from grants and foundations. We have strong support from the Rockefeller Foundation, the Hewlett Foundation, the Inter-American Development Bank (IADB) and the World Bank, among others. The second pillar of funding is based on our consulting work, which we do for the UN World Food Program (WFP), the United Nations Development Program (UNDP) and the UN Children’s Fund ( UNICEF).

You are also an expert on other technological fields like for example big data and crisis mapping. Could you explain to us the use of those for humanitarian efforts?Due to digital technology and the emergence of big data, we have to deal with an overwhelming flood of information, which abounds in social media, for example. But this hasn’t always been that way. Whenever a catastrophe happened in the past, there has been information scarcity. Now for almost ten years this problem has been changed into the opposite extreme: there is an information overload following major disasters. For that reason, humanitarian organizations have to develop effective strategies to filter relevant information more quickly in order to support decision makers. The use of artificial intelligence can help to make sense of big data by «the needles in the haystack», that is, the relevant and actionable pieces of information that are generated during disasters. Drones are also able to collect data much faster than humans.We have created cooperative partnerships with universities to leverage artificial intelligence and computer vision in order to develop automated solutions to analyze this vast amount of data.

synpulse From Outside In | 25

You founded the «Humanitarian UAV Network» and co- founded the «Digital Humanitarian Network». What are the goals of these organizations?The Humanitarian UAV Network (UAViators) provides an infor-mation and coordination service. The website connects over 3’000 members in 120 countries. UAViators has also developed a code of conduct for unmanned aerial vehicles. I co-founded the Digital Humanitarian Network with the UN. The goal there was to create an interface between established humanitarian organizations and digital volunteer groups. We have invited digital volunteer groups who can go to the website and fill out an activation form.

Could you tell us more about your personal background? According to your blog «iRevolutions» you were born and raised in Africa. Do you think that your experiences have influ-enced your career choice? I was born in the Ivory Coast and grew up in Kenya, as my father worked there for a Swiss international company. I com-pleted high school in Vienna and then started a Computer Science degree in England. However, I experienced a key moment here: When I was building logical circuits, I began asking myself whether what I was doing had any connection to my upbringing in Africa. I couldn’t see then how Computer

Science could make a difference in Africa. So that same day I decided to drop out of Computer Science and change degrees to International Relations where I could study more relevant subjects like Economics or Political Science. Ironically, in the last ten years I have worked closely with many Computer Science experts, and this is also true regarding my work at WeRobotics. So in some way I have returned to Computer Science.

Finally, what is your wish for the development of WeRobotics? What is your vision for the planet, especially with regards to the fast development of technology?My plan for WeRobotics is to establish eight Flying Labs in eight world regions over the next three years. Another goal is to enable these labs to work directly together and thus to support each other. Promoting this direct South-to-South capacity building is central to our vision. With respect to my vision for the planet: The rise of robotics and artificial intelligence will have a profound change on our world. The Global North will be the main actor in this space. Therefore, we have to ensure that the digital divide does not get bigger, where only the rich parts of the world have access to robotics technology. Our mission at WeRobotics is thus to democratize access to robotics solutions.

Dr. Patrick Meier is the Executive Director and co-founder of the NGO «WeRobotics». Over the past 15 years, he has been collaborat-ing on a wide range of humanitarian projects and has worked to-gether with well-known international organizations like the United Nations, the Red Cross, and the World Bank. He has guided the field of crisis mapping at the African NGO Ushahidi and at Harvard University in America as well. Patrick is a very popular consultant and speaker in the matter of humanitarian use of robotics. In his book «Digital Humanitarians» and on his blog «iRevolutions» he dis-cusses the possible and different ways of using digital technology for social and ecological purposes. Furthermore, he is the co-founder of the organization «Digital Humanitarian Network» and founder of the association «Humanitarian UAV Network», which supports the secure use of unmanned aircraft in a humanitarian context. Patrick has a doctoral degree from Tufts University in International Affairs.For further information see:www.iRevolutions.org and www.werobotics.org.

synpulse26 | Regulatory & Compliance

The volume of high net worth individuals (HNWI) wealth in Asia-Pacific region has hit new record highs; and is now the largest in the world. In 2015, Asia-Pacific HNWI wealth grew by 9.9%, which is nearly six times higher when compared to the growth experienced by the rest of the world (1.7%)1. Due to a growing base of clients and an increasingly strict regulatory environment, managing operational risk has emerged as a major area of concern for private banks. The potential impact of fraud on the business is substantial. According to a recent report2, a typical fraud incident may lead to financial losses ranging between USD 5-10 million and severe reputational damage. In 2011, a case of internal fraud brought about a loss of over USD 10 million to a major private bank. Front-office staff of the bank had siphoned off funds out of client accounts for many years. Similarly, in 2013, another private bank bore a loss of around USD 5 million, due to internal misconduct by front-office staff.

Banks have started strengthening their control frameworks and technology platforms to cope with the increasing

complexity of fraud attempts. Unlike retail banks, which use standard IT solutions available in the market for fraud risk management and fraud risk detection, private banks are considering bespoke fraud risk management solutions.

Private versus retail banking risk management To highlight the particulars of fraud in the context of private banking, it is useful to compare the nature of fraud in private banking to that in retail banking.

A retail banking business involves large volumes of small-sized, relatively simple transactions. As such, fraud detection capabilities are generally standardized and are often geared towards the limited scope of activities performed by mass-market clients. Technology plays a significant role in automating most detection processes and controls, forming the overall basis of the fraud controls. Ultimately, due to the large volume of transactions, fraud cases are a drag on revenues. Hence, the aim is to keep incident counts and losses low in the most efficient manner possible.

Fraud in Private Banking – Are You Protected?

Fraud has risen to be one of the key threats currently facing private banks. Besides huge financial losses, it causes reputational damage. Banks could prevent this with tailor-made technological solutions and managing fraud risk. Find out what you need to know to identify and manage your vulnerabilities.

Authors: Prasanna Venkatesan | Parsa Khoshdel

1 Source: Asia-Pacific Wealth Report 2016 2 Source: Private Banker International

synpulse Regulatory & Compliance | 27

In contrast, a private banking business involves a small num-ber of large-sized transactions. Consequently, fraud cases are infrequent, more intricate, and highly impactful. To avoid the risk of fraud, private banks have typically sought to tie their controls and processes closely together. However, with processes becoming increasingly complex, the opera-tional cost of maintaining checks and balances is also rising. Fraud in private banking typically arises from operational gaps that provide opportunities for abuse. However, due to the additional services offered to HNWIs, the risk of having such gaps is correspondingly larger. A few common examples are:

Forging clients’ identity to take over control of relatively vulnerable dormant or hold-mail accounts. Such cases may occur due to lack of controls such as a lack of callback checks for client verification.

Fraudulent transfers and unauthorized trades, particularly with repeated transfers concerning smaller amounts since these often do not involve four-eye checks or independent verification checks.

In both scenarios, the fraudster may reside either inside or outside the bank. To reduce the risk of such cases occurring, it is imperative to minimize the gaps in the bank’s checks and controls. Maintaining purely manual operational controls is becoming increasingly difficult and expensive. Enhancing the size of control units and sales surveillance often stymies effi-ciency and adds complexity. Therefore private banks have steadily turned to new software tools to complement their operational controls, thereby enhancing their ability to detect and prevent further cases of fraud in a scalable way.

Introducing technology in fraud risk managementSoftware solutions tackling fraud detection span across a wide range: from off-the-shelf tools, complete with detection and case management functionality, to purely technical platforms that are highly customizable for implementing fraud detection solutions ( 1).

In terms of maturity and sophistication, initiatives undertaken by banks are diverse. Some opt to use off-the-shelf software to automate the consolidation of data and certain manual checks

1: Categorization of the Market’s Fraud Analytics Platforms

Source: Synpulse

Patt

ern

reco

gniti

on (s

ophi

stic

atio

n)

Less

soph

istic

ated

Mor

e so

phis

ticat

ed

More customization required Off-the-shelf products

Ease of implementation for private banks

Programming language Build-up required State-of-the art technology Workflow not available Open sourced Community support available

Off the shelf solutions (challengers) Less to no build-up required Allows bank specific changes Technical support available

Data science platform Build-up required Sophisticated, with programming language extensions Workflow available Visual programming Technical support available

Off the shelf solutions (industry leader) Less to no build-up required Sophisticated Allows bank specific changes Technical support available Very expensive

Off the shelf solutions (niche players) Less to no build-up required Less sophisticated Allows bank specific changes Technical support available Area focused, i.e. audit

synpulse28 | Regulatory & Compliance

to flag suspicious activity. Others are using data science platforms that offer a lot of technological agility to build business rules and sophisticated algorithms on the platform. Lastly, some banks are pursuing custom-built solutions from the ground up, such as the joint venture «Signac», between «Credit Suisse» and «Palantir»3, which aims to detect unau-thorized trading or other suspicious internal activities.

Currently, the trend for large multi-national private banks has been slowly shifting away from off-the-shelf solutions towards bespoke fraud prevention platforms. These are highly custom-izable and offer significant capabilities in analytics. This enables the bank to process substantial amounts of data using an automated tool, replacing manual processes handled by different departments. More sophisticated checks can be implemented to replace labor-intensive tasks.

Deciding on a suitable fraud analytics platformAs highlighted in 1, private banks can choose from a wide range of solutions when selecting a suitable fraud analytics platform. Unfortunately, within the range of off-the-shelf

products, few are designed exclusively for private banks. Due to limited potential for customization, the product adds unnecessary bulk and complexity in the form of excessive functionalities that are not applicable to private banking processes. Additionally, the important nuances that need to be applied in the private banking context are overlooked.

On the other hand, the development of an in-house platform from scratch is likely to be time-consuming and expensive. As an optimal alternative, private banks should adopt a hybrid approach. They can opt for a solution with a high degree of customizability while leveraging a pre-defined analytics framework consisting of fraud scenarios, pattern recognition and risk-scoring methodologies.

The hybrid approach enables risk managers to customize pre-defined fraud scenarios based on the bank’s existing processes and known control weaknesses. The next step of developing an effective risk scoring methodology across these scenarios becomes much faster as the tool would have pre-built capa-bilities to run simulations using statistical methods such as

3 Source: www.palantir.com/pt_media/credit-suisse/

2: A High-Level Overview of a Fraud Analytics Platform’s Structure

Source: Synpulse

Scenario-basedpattern analysis

Analytics engine

Transactional data

Client static data

Historical data

Blacklist Whitelist Watchlist

HR data

Independent verification data

Special client data

Control list

Database

Reporting

Escalation

Suspicious activities

Data sources

Fraud detected

Management

Yes

No

Valid?

Case management

2ⁿᵈ Line investigation

No issuedetected

MI reporting

Fraud analytics platform

New activity

synpulse

Authors

Regulatory & Compliance | 29

sampling, and false positive reductions. Finally, the hybrid approach also offers case management and management reporting functionality, which can be integrated into the bank's fraud risk management processes.

Defining risk: the core of a fraud analytics platformBanks usually set up dedicated fraud controls for individual processes which results in incidents being investigated independently of each other. Fraud cases, however, usually comprise multiple steps, taken by the fraudster to bypass such controls. They involve various transactions and changes to the bank's records, such as HR or client data. Due to the isolated nature of investigations, connections between such steps are often overlooked. A fraud analytics platform attempts to bridge precisely these gaps.

The platform will typically ingest various kinds of data from several sources: client data, transaction data, HR data, etc. and by applying the built-in scenarios against this data, it can identify potential cases that would need further investigation. Using dynamic control lists, the platform can eliminate false positives and reduce the effort required to analyze suspicious cases. In effect, 2 illustrates how the various components mentioned fit together in the fraud analytics platform’s architecture.

However, what truly differentiates a fraud analytics platform from the bank’s internal controls is the smartness of the platform’s risk scoring methodology to highlight the truly

suspicious cases by connecting the dots based on the overall client, risk management and portfolio activities and at the same time eliminating false positives effectively.

Fraud risk management: a shared responsibilityApart from a strong fraud analytics platform, effective fraud detection requires clear, pre-defined action plans for identi-fied cases. Fraud case management can be a sensitive topic among staff, and care must be taken to treat such issues with respect. Project teams must ensure ample buy-in from across all levels of the organization as a source of support for the initiative. Working level teams must also be instructed to remain flexible and maintain a sense of trust with the market-side staff under investigation. The fraud case management team must include team members who have existing rapport and trustful working relationships with the front office.

ConclusionThe challenges that private banks face in fraud risk management are rapidly changing. Synpulse has been at the forefront of working with stakeholders at leading private banks in developing and optimizing frameworks for fraud risk management. With the threat of regulatory fines, reputational and financial risk due to fraud, banks are looking to strengthen their overall framework over the next few years. Innovative technologies and analytics tools will play a pivotal role in enabling banks to tackle various topics within the areas of risk management and compliance.

Prasanna Venkatesan Associate Partner (Synpulse Singapore)prasanna.venkatesan@synpulse.com

Parsa Khoshdel Senior Consultant (Synpulse Singapore)parsa.khoshdel@synpulse.com

synpulse30 | Regulatory & Compliance

IFRS 9 – A Paradigm Change in Financial Reporting?

The reporting standard «IFRS 9» is imposing significant changes in financial reporting on financial institutions. Particularly impairments are now treated very differently than in the past. Functional and technical implementations as well as procedural aspects are decisive factors and need to be optimized for future success.

Authors: Florian Köller | Daniele Abbruzzese

Without any doubt, the financial services industry has been facing an increasing level of audits and investigations over the last decade. This can be contributed to the aftermath of the financial crisis of 2008, when complex new financial products and services emerged. With these developments, it also became increasingly difficult for regulatory bodies, audit companies, and other stakeholders to assess the financial health of the companies.

Governments and regulating bodies felt the need to control the behavior of banks in a more stringent manner and aimed at ensuring a healthy and functional financial sector through new guiding measures. Also, tax authorities used the window of opportunity to raise tax transparency and reduce tax evasion through regulations such as the «Automatic Exchange of Information» (AEOI) and the «Foreign Account Tax Compliance Act» (FATCA).

Changes in the reporting standardIn line with these overall market trends, in the area of financial reporting an update of the «International Financial Reporting

Standards» (IFRS) was issued by the «International Accounting Standards Board» (IASB). In general, IFRS enforces comparable balance sheets over different legislations. Internationally, it has been adopted by numerous countries and is obligatory for listed companies in particular. The current standard «International Accounting Standard 39» (IAS 39) dates back to 1998. Over the course of the years, financial markets have changed and new financial instruments have been created. To properly catch up on these developments, several improve-ments and additions to the accounting standard were released. The economic crisis increased the pressure for a major revision of the regulation, and after years of detailed definition, the IASB issued «IFRS 9 Financial Instruments» in 2014. As of January 1, 2018, IFRS 9 will be mandatory for banks and insur-ance companies whose reports are based on the European IFRS or «Generally Accepted Accounting Principles» (GAAP)1, developed in the United States.

Particularly the recognition of expected losses was in focus after the economic crisis. Until now impairments were based on historic experience as losses occurred. In order to make

1 Source: IASB

synpulse Regulatory & Compliance | 31

banks more robust for difficult conditions, a model was devel-oped to change the current approach to a simulation-based, forward-looking approach. The following fields are affected by IFRS 9:

Classification and measurement of financial assets

Impairment calculation

Hedge accounting

What is newClassification and measurement of financial assets in the future will depend on two things: On the one hand, on contractual cash flows, meaning sole payment of the principal and interest or other forms of compensation. Particularly this focus on product cash flows distinguishes the approach from today’s regulation. On the other hand, the business model of an asset is considered. The term «business model» in the context of IFRS 9 refers to how financial assets are managed and the intention as to whether positions should be held until maturity, sold, or both.

Furthermore, the impairment model under IFRS 9 results in an earlier recognition of losses by switching to an expected loss-based approach from an incurred loss-based approach. Banks will be required to consider macroeconomic information when calculating expected credit losses. Based on this new approach, the complexity of provision calculation increases significantly. The reason lies in the required simulation element, while so far a simple calculation upon occurrence was sufficient.

Banks will be required to consider macroeconomic information when calculating expected credit losses.

In comparison with impairment and classification, the hedge accounting changes seem less critical for financial institutions. The corresponding requirements will reduce complexity. They allow entities to apply hedge accounting more broadly, the effectiveness test is simplified and more types of assets qualify for hedge accounting.

1: IFRS9 Challenges in Operations, Controlling and Financial Reporting

Source: Synpulse

Business model impacting risk management and collateral management

Close link between controlling, treasury and risk management for credit risk processes required

Initial impact on provisions Potentially higher volatility Increased disclosure

Controlling

Operations Financial reporting

synpulse32 | Regulatory & Compliance

What is required?The regulatory framework is expected to have high organiza-tional, technical and operational impact ( 1) as the changes require adaptations in several functional areas of the organi-zation. The implementation of IFRS 9 will undoubtedly need a closer integration of different functions and skills (finance/treasury, accounting, risk management, and quantitative modelling). This is due to the overarching requirements which affect different parts of the organization, not only accounting teams. Consequently the preparation of a new methodological framework (for loans and guarantee contracts), policies and processes is an opportunity for any organization to foster closer collaboration. From a change management perspective a skilled, multidisciplinary project team is required for a successful and smooth transition to IFRS 9.

Organizational impactThe initial setup of the necessary data can pose a challenge to organizations: The initial classification of financial assets is to be closely derived from corporate and credit risk strategies. When considering dependencies on processes, such as credit risk management, the IFRS 9 implementation needs to ensure consistent calculations, data flows and external reports to make sure, that all processes, e.g. credit risk management, are alligned.

To ensure compliance with IFRS 9, financial institutions also have to implement new processes such as a control frame-work to fulfill the new disclosure requirements. For this pur-pose, the existing credit risk models (e.g. incurred loss model) need to be amended and a new end-to-end process should be designed and introduced. Besides the implementation, also training and building up know-how in the organization are recommended best-practice: They bridge the gap of the interdisciplinary requirements posed by IFRS 9 and ease collaboration.

Institutions can leverage an IFRS 9 implementation to introduce a

centralized and fully integrated end-to-end impairment calculation.

Currently, in many banks and financial institutions the impair-ment processes are handled slightly different by each location or business unit, which raises the complexity of a project,

as various processes and local solutions must be revised and amended. This aspect needs to be factored in and offers the opportunity to standardize processes across all locations.

Institutions can leverage an IFRS 9 implementation to introduce a centralized and fully integrated end-to-end impairment calculation. This eases compliance with IFRS 9 regulations through all business units and geographical locations. Another advantage is a reduction of the implemen-tation effort involved on a local level and the leveraging of economies of scale. Otherwise every decentralized system component would have to comply accordingly.

IT impactWith the technical changes, due to IFRS 9 and the increased disclosure obligations raised in the recent past, entities are confronted with an increased volume of information being required. This information may not be easily and readily available from current systems. In the past they may not have captured and maintained data at the level of detail required under IFRS 9 (one potential option may also be to rely on external data if available).

The implementation of IFRS 9 there-fore poses significant challenges to

banks and financial institutions, on data models as well as on the IT

infrastructure.

Based on these requirements, many financial institutions will need to collect and analyze additional data on their positions and implement changes in their systems. For example, the new standard for impairment calculation will tremen-dously affect how credit losses on loan portfolios are accounted for. The expected impairment loss model will most probably lead to bigger provisions. It could even lead to more volatile provisions, as they will depend on macroeconomic factors rather than the individual credit quality.

The implementation of IFRS 9 therefore poses significant challenges to banks and financial institutions, on data models as well as on the IT infrastructure. The new expected credit loss approach make necessary both new data attributes (such as collateralization or new IFRS 9 impairment stages) and large amounts of data and complex calculations for simu-

synpulse Regulatory & Compliance | 33

Authors

lating the expected loss. Integrating those attributes into the current platforms can represent a challenge in terms of complexity, effort and consequently higher costs. Additionally, it may be required to establish a setup that is fit for future changes due the inability of current systems to capture the needed data. This may call for integration with new or additional software modules.

Based on the past projects, establishing comprehensive data management can ensure that all necessary data is available. Data governance structures and controls improve quality because the required data is often sourced from various IT systems and may necessitate cleansing before it impacts calculations.

Best practicesAlthough IFRS 9's mandatory effective date of January 1, 2018 may seem still some way down the road, banks are requested to introduce IFRS 9 parallel to other regulatory projects (e.g. MiFID II) at this time. Additionally, banks may also depend on their software vendors to deliver the basis for IFRS 9 and

hence are exposed to considerable time pressure. Standardization, data governance, and close collaboration have proven to facilitate projects. Besides, institutions are well advised to assess the expected impact on reported results early on. Therefore, running IFRS 9 parallel to IAS 39 this year, would allow a comparison of the impact over a certain period and adaptations could be made prior to IFRS 9 being effective. Due to the changes regarding audited data and procedures, proactive information to auditors is advisable.

From a technical perspective, data availability and quality challenges should be the focus of attention from an early stage on, as static data is the key for all changes that IFRS 9 brings along. Besides the conceptual changes, IT landscapes and processes in finance and risk in general are expected to require a higher level of flexibility going forward. Amendments of IFRS 9 in the future would particularly impact modifications of for-ward-looking information. Therefore developing a clear target picture for business and IT in order to guide the implementation of a robust and efficient end-to-end process is essential.

Florian KöllerManager (Synpulse Switzerland)florian.koeller@synpulse.com

Daniele AbbruzzeseAssociate Partner (Synpulse Switzerland)daniel.abbruzzese@synpulse.com

synpulse34 | Regulatory & Compliance

In Asia, two large-scale tax amnesty campaigns aroused the finance world’s attention: one in India in 2016 and another in Indonesia that ended in March 2017. The campaigns offered a window for taxpayers to declare previously undeclared wealth and pay a special tax, in return obtaining freedom from pros-ecution over their unmet tax liability. This was p articularly attractive due to the increasing exchange of tax information between jurisdictions, under regulations e.g. FATCA1 and CRS.

CRS, the OECD2 version of FATCA (US), or CDOT3 (UK), is a cross-jurisdictional regulation that aims to standardize the e xchange of client tax information globally. It was first endorsed by the OECD in 2014.

Reporting solution readinessAlthough reporting is not scheduled to start before 2018 in Asia, Financial Institutions in Singapore and Hong Kong

already start to prepare, as compliance with CRS requires both operational re-engineering and technological transformation. On the operational side, client onboarding processes need to be revised while ensuring that pre-existing client remediation happens with minimum friction to client experience. Further-more, changes are necessary for core banking platforms and customer relationship management (CRM) systems to capture client tax information in a structured manner.

Three unique challenges presented by CRSThe high volume of reporting data may require widespread enrichment or cleansing exercises, which in turn increases the risk of erroneous reporting. The freedom offered by the OECD poses a further challenge, as it allows the participating juris-dictions to choose local reporting formats. This adds to the organizational and technical complexity that FIs will need to cope with.

CRS – Choosing the Correct Reporting Model Is Half the Job Done

The scale of Common Reporting Standard (CRS) is unprecedented and reporting of tax information is scheduled to start for most Asian jurisdictions in 2017 or 2018. For financial institutions (FI) who haven’t done so yet, it is advantageous to design and implement a solid reporting model that can handle the scope and complexity of the regulation.

Authors: Cherry Hong Pei | Yash Shah

1 Foreign Account Tax Compliance Act 2 Organization for Economic Co-operation and Development 3 Crown Dependencies and Overseas Territories International Tax Compliance Regulations

synpulse Regulatory & Compliance | 35

Choosing the right reporting model is the keyConsidering the unique challenges, tight timelines and the high likelihood of regulatory changes in the near future, it is clear that an effective and flexible target reporting model for CRS is critical. The key reporting steps are common and need to be performed by each FI. However, the implementation of the reporting process can be done in various ways, especially for FIs with an international presence. At a high level, effective reporting models can be categorized in three groups: the local, regional, and the central model. Each has its own advantages and disadvantages. All three reporting models are widely used by FIs for FATCA reporting, and each can potentially be applied to address CRS reporting. The diagram presents the drivers that motivate an FI to choose a particular model, as well as the implications in terms of scalability, flexibility, and reporting consistency. The solution consideration section describes two approaches from business and technical aspects an FI may take to mitigate the weaknesses of the chosen model. The three main drivers that relate to the current situation of the FI are: technological infrastructure, business and organi-zational setup, and implementation constraints such as time-line, resources, and cost. The implications of each model are evaluated according to three criteria: scalability, flexibility, and global reporting consistency. These are particularly rele-vant for CRS reporting due to its scale and dynamic regula-tions. For FIs with international presence, branches which are currently not affected by CRS regulations may need to be compliant in the future. Hence, the CRS reporting model should be scalable enough to be rolled out to other branches. Furthermore, CRS regulations are subject to irregular and sudden changes. These can affect jurisdictions globally when changes are imposed by the OECD, or locally when imposed by a particular local regulator. Reporting models therefore need to be flexible enough to be able to adapt to either kind of change. Lastly, the reporting model has to ensure global consistency of reporting, since an FI operating internationally carries one name.

The local modelThe evaluation of the local model shows that the main drivers are a local technological and organizational structure: Devel-opment and maintenance of applications are done locally, with often very different CRM systems and reporting systems in use for each branch. In this kind of application landscape, client data is sourced in each branch and captured in individual systems. Similarly, locally organized tax advisory teams and regulatory reporting processes can drive the selection of a CRS

reporting model towards the local model. From an implemen-tation perspective, the local reporting model is advantageous because it requires a shorter timeline. It needs fewer r esources, costs less and hence has the lowest implementation complexity of the three models. However, the implications of this model are a low scalability and flexibility in adapting to global requirement changes. It also has a high chance of global reporting inconsistency. To compensate for these weaknesses, FIs should target to align and monitor the various implemen-tations globally. Imposing global implementation standards through a global tax office is recommended in this regard. Synpulse’s past experience shows that the local target reporting model is mostly chosen by FIs whose branches operate relatively independently in markets in various parts of the world.

The central modelThe weaker aspects of the local model are those where a central model is the strongest. It is highly scalable to other locations, flexible in adapting to global regulation require-ment changes, and can maintain a high level of global report-ing consistency. The main selection drivers for this model are a global infrastructure setup and a global reporting process. Client data can be sourced in each branch separately, but is to be stored and controlled centrally. A global tax advisory team is also of key importance for this model to work. The imple-mentation timeline for the central model is the longest, consumes the most resources, and has the highest cost of the three models. To address these points, FIs are strongly recom-mended to start project planning early and accurately. Leveraging a third party automated reporting solution is essential to reduce implementation complexity and save costs. Such automated solutions should be able to automatically draw data from source systems, comb through them, present them in the appropriate formats, and deliver the reports to specific places at specific times. They can help to increase the operational efficiency and reduce human errors. For the other two models, automated reporting solutions are useful, but may not be of critical importance. The central reporting model is primarily recommended for FIs with a strong presence in one jurisdiction and a few branches in other regions.

The regional modelThe regional model is a hybrid between the local and central model. It is suitable for FIs concentrating their activities in only one or two regions (e.g. APAC, EU). A regional IT setup in

synpulse36 | Regulatory & Compliance

1: Three Reporting Models

Source: Synpulse

Reportingmodel

Description

Technologicalinfrastructure

Scalability

Flexibility

Global reporting

inconsistency

Business & organization

setup

Timeline, resources &

costs

Business

Technical

Selection drivers

Implications

Solution considerations

Local Regional Central

UK

CHJP

SG

AU

IT

UK

CHJP

SG

AU

IT

UK

CHJP

SG

AU

IT

Each branch performs the entire reporting process independently

No dependency & no collaboration between branches

Reporting implementation projects are run independently

Application landscape is set up locally. Each branch has a different core banking system

Low scalability to other locations due to the localized approach

Implementation is driven locally. A global tax advisory office should be set up to monitor & interpret regulations, & advise individual branches thereon, in order to ensure consistency between branches

Focus on reporting consistency & cross- leveraging of solutions among branches. Solutions addressing common component of CRS applicable to all branches may be reused & locally customized

High/low flexibility in adapting to changes in local regulations/to global regulatory changes, applicable to all branches

High chance of global reporting inconsistency & related reporting errors

Existing reporting process only involves local teams. Local tax expertise exists

Timeline to meet regulatory requirement is short with limited resources & tight budgets

Application landscape is set up regionally.A common core banking system is shared among branches

High/low scalability to other locations within the same region/in different regions

Implementation is driven regionally. A global tax advisory office should be set up for the same purposes as in the local model: to ensure consistency between regional offices

The optimal solution for the regional model lies between those for the local & central models in terms of flexibility & regulatory scope coverage

Low/medium flexibility in adapting to changes in local regulations/to global regulatory changes

Low to medium chance of global reporting inconsistency & related reporting errors

Existing reporting process involves a regional team. Local & regional tax expertise exists

FIs have some time to meet regulatory timeline. Some resources are secured with fixed budgets

Application landscape is set up globally.Most of the data is captured & controlled centrally

Highly scalable to other locations

The global tax office should drive the implementation & coordinate the solution’s adoption across branches, while individual branches play a primarily consultative role

Leverage an automated reporting solution to handle reporting volumes. Focus on coverage of the regulations applicable to FI’s branches, while ensuring flexibility for frequent changes to regulations

Low/high flexibility in adapting to changes in local regulations/to global regulatory changes

Very low chance of global reporting inconsistency & reporting errors

Existing regulatory reporting is performed centrally. Global tax office exists

FIs have sufficient time to meet regulatory timeline. Major resources are secured with flexible budgets

Branches located in the same region, e. g. Asia Pacific, perform the data preparation, report generation, & post-submission governance steps regionally in one branch such as SG

Data sourcing & validation remains the individual responsibility of each branch

Only the data sourcing will be performed by each branch independently

A global centralized reporting tool is used to handle the data preparation, validation & reporting submission, track the reporting status & handle the post-submission governance

synpulse Regulatory & Compliance | 37

Authors

Cherry Hong Pei Manager (Synpulse Singapore)cherry.pei@synpulse.com

Yash Shah Senior Consultant (Synpulse Singapore)yash.shah@synpulse.com

this context is characterized by shared CRM- and reporting systems between branches within each region. Client data can be sourced locally but are stored and processed at a regional level. For this model to be effective, organizational require-ments include the presence of a regional reporting process and expertise. The regional model is more expensive and takes longer to implement than the local model. It requires regional alignments of people, processes, and technology. The main advantage is that it is easily scalable to other branches in the same region. Furthermore, the chance of global reporting inconsistency is much lower than the local model.

ConclusionIn an ever-evolving global regulatory landscape, CRS poses major challenges to FIs. The volumes involved, technical complexities and dynamic regulations make it exceptionally difficult to define a reporting model capable of meeting the regulatory reporting goals:

Achieve compliance globally

Uphold client experience by minimizing adverse regulatory impact

Develop reporting processes that are cost effective, flexible and sustainable

It is important that an FI considers its current IT infrastructure, business and/or organizational setup. The feasibility of imple-menting any type of reporting model must be evaluated against these factors. In fact, no single model fits all the FIs’ needs: even FIs running very similar operations within the same region have chosen different reporting models. With the start date of reporting under CRS fast approaching, FIs gain competitive advantage by preparing well and carefully assessing which reporting model to opt for.

synpulse38 | Operational Excellence

The current fragmentation in the private banking (PB) and wealth management (WM) industry is not necessarily negative in itself, but too many and too small players can suffer with revenues lagging behind managed assets and often behind growing costs. This incentivizes everyone into up-scaling mode, creating the observed exponential increase in M&A activities in the sector.

Fragmented landscapeThe UK wealth management sector has emerged and evolved in specific ways that bear resemblances to the rest of the world, but also significantly differ for historic reasons and today present a unique amalgam of firms and roles in the market. Private banks are solidly present and recognized, both native institutions and subsidiaries of foreign private banks (or private banking arms of multinational universal banks). They, however, do not dominate the sector. There is a separate and unique breed of wealth management firms (sometimes called «investment management» or «asset management» but with a distinct focus on private wealth). Many have their historic roots in traditional brokerages,

and some have evolved from accounting firms. Today, some UK wealth managers exceed in size (client base and AuM) the average private bank, and the segment as a whole outnumbers the banks. The regulated role of retail financial advice providers, in particular the IFAs, also differs from similar independent professionals elsewhere (e.g. the Swiss «external asset managers», or the Registered Investment Advisers (RIA) in the US). Some have ceded their independence to tie up with primary providers (or large distributors/wholesalers of finance products), and act effectively as their client-facing front. Adding to the picture are insurance players in long-term protection segments like «life» and «pensions», where the product has a distinct investment nature and the boundary with private asset management blurs to the extent that many insurers now have «asset management» or «wealth management» subsidiaries.

When this typology is seen from the perspective of size, a full spectrum from the single independent individual to the giant asset managers and global banks, completes a picture of massive diversity, with less-than-clear demarcation lines.

Scaling the Wealth – Consolidation in the UK Wealth Management Industry

The private banking and wealth management industry in the UK is changing significantly. Having historically evolved into a diverse ecosystem of companies, it responds to external challenges through scale. Mergers and acquisitions between firms are arduous undertakings, but organic growth takes too long for the rapidly changing market conditions.

Authors: Vladimir Dimitroff | Aastha Dhawan

synpulse Operational Excellence | 39

Through most of history such fragmentation has been sustainable: consolidation always happened, but until recently was not a burning imperative. Today analysts and practitioners alike agree that in the UK market there are too many sub-scale players. Even a narrowed classification of private wealth managers yields in excess of 150 firms (excluding IFAs). We take a look at how this is changing.

Drivers of the industry consolidation «Size Matters» was a teaser headline we used recently to intro-duce the third «Senior Executives Forum on Consolidation»1. There we predicted that «scale» will become a most frequent buzzword and explanation of why industry players acquire (or get acquired by) others. Scale, however, is not a goal in itself, there are some known root causes that can potentially be addressed by scaling up.

First and foremost, we cannot ignore the market conditions. Among them low interest rates, competitive price pressures and increasingly informed and demanding clients all present a challenge for the revenue yields on managed assets (AuM). Fees and resulting margins are squeezed too low for comfort. Then there is regulation. Well intended to prevent financial turmoil and to protect consumers, piles of regulatory require-ments mean more complex and resource-intensive processes, monitoring, enabling technology investments – all adding to the cost base. At the same time required transparency of charges and other restrictions on revenue streams mean further limitations on profitability and downward pressure on

shareholder value. This makes cost savings a very acute objective and the expectation that scale can improve the cost base is driving the M&A appetite.

We conducted a study of 38 M&A deals in the wealth manage-ment sector announced in 2017 and, among other stats, combed the press releases and CEO interviews for some key-words to infer the motivation behind the deals. «Scale» was by far the top driver, followed by reaction to «market conditions», «improving the firm’s offering», «regulation» and «diversifica-tion». It should be noted that these terms overlap and have dependencies, hence they cannot constitute a clear taxonomy. Most of the others are subordinate to scale, representing challenges for which it is a perceived solution. Nonetheless, this is a strong indicator of the strategic goals of many industry players and the decision process to undertake M&A actions.

The path correlating other variables to scale usually goes through the cost objective. If we remove scale from the picture completely, the cost base would clearly dominate. We also ran a small survey with 31 executives from the sector, and according to them the main drivers for consolidation are as shown in 1. Clearly all these objectives can be achieved through carefully considered and constructed upscaling of the business.

The rapid advancement of digital services and business models is mostly seen as a cure for the other consolidation drivers, rather than one of them. Indeed, Robotic Process

1: Main Driver of Consolidation (%)

Source: Synpulse summer survey, June 2017

1 The 2nd Senior Executives Forum took place in March 2017 in the historic Barber-Surgeons’ Hall in London. Learn more about it in The Magazine 2, 2017.

Cost synergies

Regulation

Innovation

Market synergies

0 5 10 15 20 25 3530

synpulse40 | Operational Excellence

Automation (RPA) is a proven cost-reduction strategy, and digitally enabled omnichannel front ends improve user experience and help to retain customers and their wealth. Digital wealth management, however brings to the market swarms of disruptive new players and creates an overload of choices. Eventually, the public is attracted to the best performers available from the most popular (i.e. most scalable and widest-reaching) platforms. «CREATE-Research» and «Dassault Systèmes», in their latest study, liken this process to the «winner takes it all» scenario that disrupted the music industry in recent years. They surveyed 450 wealth managers with over USD 30 trillion in global AuM – and a third of the respondents expect their industry to be disrupted by fintechs. Quite a few of those in the study expected their incumbency to prevail, but history teaches us that denial is not the best strategy.

The consolidation players Who consolidates – and how? It is tempting to describe consolidation as a «food chain» – a somewhat cynical view to which we prefer «value chain». At the bottom, small-to-medium wealth management firms are busy attracting and absorbing the lowest unit in the trade: the IFA. Acquiring the business of several (or several hundred) IFAs is a good way to climb the ladder with benefits to every party. The scale achieved in this way, has the additional benefit of turning the bidder into a more attractive target. Up the chain the bigger bidders have plausible incentives to acquire larger targets: the name of the game is scale.

«A firm should be agnostic as to whether it’s buying or selling – it’s all about scale», said Ashcourt Rowan (then) CEO Jonathan Polin at the time they were acquired by «Towry». Later they were in turn bought by «Tilney Bestinvest».

Apart from the industry players themselves (private banks and wealth management firms), notably active and helping to fuel this consolidation trend are financial investors, primarily private equity (PE) firms. For them acquisitions are not an end in itself, but a move up the chain – often with lucrative profit. They may not just sell an acquired target after optimising it and making it more attractive, but they can even merge two acquired firms before offering the combined entity upstream.An example of this PE approach is the case of «Bridgeport», who acquired «Quilter & Co.» and «Cheviot Investment Management» separately, merged them, and then sold «Quilter Cheviot» to current owner «Old Mutual».

In the fuller landscape of wealth M&A players, there are a couple of odd, but nonetheless important ones. An obvious target for many banks (and to a lesser extent – wealth management firms) are the very disruptors they are trying to resist. A fintech is becoming a popular acquisition for those lagging behind in their digitalization (and many in the PB and WM sector are), it is a rapid addition of critical capabilities, a safeguard against disruptors, and a new «door» into the wider mass-affluent segment below high net worth individuals (HNWIs) – all this at an affordable (for their scale) price. A para-dox is that the reverse can also happen: in a «man bites dog» scenario, an ambitious fintech challenger can target a smaller (or distressed) bank and thus shorten their path into a desired market. This is exactly what we saw in recent weeks, as chal-lenger «Tandem» successfully bid for «Harrods Bank». This may not be the last and only case in these interesting times. Another counter-intuitive paradox is the effect of Brexit on the sector. Prevailing assumptions (and observations) are about financial institutions seeking to abandon the City for other European financial centres. This is true, but mostly for invest-ment banks. At the same time no less than four major Euro-pean private banking players: «Credit Suisse», «Pictet», «UBS» and «Societé Générale» all declared to Bloomberg and the Financial Times that they plan to increase their UK presence. They see plentiful evidence that wealthy global citizens prefer vibrant London to Switzerland, especially when recent laws remove the famous secrecy. More important, a weaker pound sterling makes many assets cheaper for them and easy to add to their global pools. One more trend to watch closely. With all the «fringe» actors, it is still the mainstay players accounting for the majority of recent deals. Wealth management firms and private banks between them dominate the M&A scene.

At present the WM firms, unique to the UK market and apparently in greater need for scale, are twice as active as private banks. Deals across them are quite rare, but with scale this is likely to change.

A glimpse of the future landscape It is easy to predict that opposite to the current fragmented state, the future wealth management market will be consoli-dated. The question is: how consolidated? Which players will dominate? Where is the balance point after which healthy consolidation becomes a monopoly or cartel? The last scenario may sound gloomy but is rather unlikely. First and foremost regulators take care to prevent monopolies, but more importantly – the wealth market is too far from such a

synpulse Operational Excellence | 41

Authors

Vladimir DimitroffPrincipal (Synpulse United Kingdom)vladimir.dimitroff@synpulse.com

Aastha DhawanAssociate Consultant (Synpulse United Kingdom)aastha.dhawan@synpulse.com

state. With a solid middle tier of multiple players and a growing long tail of ambitious challengers, the current number of 150 may drop to 100 or below, but it is highly unlikely to drop to just a handful of quasi-monopolists. In our summer study we asked our 31 industry guests how many players they expect to be active in 2020 ( 2).

The sample of respondents is small, but given the seniority of the group it is noteworthy that some even expect the number to grow. It is possibly a matter of which moves faster: the con-solidation or the new fragmentation from an influx of challengers. One thing is certain about the future: wealth management will never look the same. Digital capabilities, innovative business models, connected and knowledgeable clients – all this is already changing the character and structure of the industry. Change is the only constant and beyond the

scale we discuss in this paper, we think that the ability and willingness to change will determine the future industry leaders.

Size does matter, after all. And scale is the name of the game – the «economies of scale» from classic economics are ampli-fied in the current conditions by subtle but important effects. The scale also enables qualitative improvements like faster and more effective innovation, diversified market strategies, and exciting ideas for even more scale. The scope of this paper did not allow for coverage of scale-dependent and scale-enabling aspects such as technology platforms or target operating models – but a strategically minded company would have the concepts and resources to develop all aspects and benefit in multiple coherent ways.

2: Expected Number of Firms in 2020

Source: Synpulse summer survey, June 2017

Between 75 and 100

Between 100 and 120

More than today

The same as today (~150)

0 10 20 504030

MastheadThe Magazine is published three times a year (English edition). Articles can be accessed via www.synpulse.com. Published by: Synpulse Management Consult-ing | Editor: HBS International GmbH | Realization: Synpulse Management Consulting | Printer: Neidhart + Schön Print AG | Feedback and inquiries to: Synpulse Switzerland AG, Thurgauerstrasse 32, CH-8050 Zurich, phone +41 44 802 2000, fax +41 44 802 2001, info@synpulse.com | Copyright: The reproduction of articles is permitted with the agreement of the publisher if the source is acknowledged. Articles by guest authors do not necessarily represent the opinion of the pub-lisher. | Photos: Shutterstock, Inc. | Layout/Illustration: HBS International GmbH

44 | Rubrik synpulse

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GermanyHamburg | Frankfurt | Ulm

United KingdomLondon

SingaporeSingapore

Hong KongHong Kong

USANew York

info@synpulse.comsynpulse.com