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Know Your Trader (KYT) Analytics Services Identifying rogue trader and compliance risks by focusing on the information flows

Know Your Trader (KYT) Analytics Services - EY

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Know Your Trader (KYT) Analytics ServicesIdentifying rogue trader and compliance risks by focusing on the information flows

1 | Know Your Trader (KYT) Analytics Services

Given recent regulatory actions that have focused on the flow of information between people, financial services companies are looking for more effective and less

costly compliance risk identification techniques that go beyond looking at trade data only.1 Regulators like the SEC, ASIC, other policing bodies and internal compliance functions have historically focused their analytics resources developing sophisticated ways to monitor and detect unusual trading patterns. This focus on trading activity is an important approach to locating suspicious transactions; however, the problem for the investigator often lies in identifying trades that may have been based on actual material non-public or sensitive information.

Our KYT Analytic Services apply statistics, mathematics, text mining, computational linguistics and the experience of financial service professionals to identify employee communication patterns through the use of data analysis, along with traditional compliance monitoring tools.

Selecting the appropriate tests with our clients, KYT Analytics Services organises related data and builds models of relationships among and between people, documents and events, giving management improved visibility into high volumes of disparate data generated from the activities of portfolio managers, analysts, traders, sales professionals and management. KYT Analytics Services can be customised to assist with early risk identification, including rogue trader patterns, breaches of material non-public information, fraud risk, bribery, kickbacks and other employee misconduct.

How it worksWorking with our clients, we identify tests based on their risk profiles and leverage an extensive library of analytics that include free-text data sources, such as emails, instant messages and documents. We also target other sources, including structured data sources like trade and order data.

By modeling the overall fact patterns of communication between relevant individuals and those proximate to them, we can analyse communication patterns over time, according to specific discussion topics and key words. We can use and present this information to management in a highly visual and objective format for evaluation and decision-making.

KYT Analytics Services can provide visibility into aberrant patterns of behaviour, in which people take otherwise routine conversations “offline”; switching to a communication channel that is less likely to be recorded or meeting a person for direct conversation. Our services can be flexible and tailored based upon the analytics needed by each company and each situation. While the engine behind KYT Analytics Services is technology-based, the concepts are co-developed by the client and a team at EY that can address the company’s specific business rules in the analytics so that risks can be identified sooner. The KYT Analytics Services team draws from a wide range of complementary professionals including PhD computational linguists, forensic data analysts, anti-fraud professionals and computer scientists who are knowledgeable in the financial services industry.

EY’s KYT Analytics Services apply statistics, mathematics, text mining, computational linguistics and the experience of financial service professionals to supplement proven compliance monitoring tools.

What is KYT Analytics Services?

1“ U.S. Widens case against Rajat Gupta,” Wall Street Journal. February 1, 2012.

2 Know Your Trader (KYT) Analytics Services |

Working with our clients, we identify tests based on their risk profiles and leverage an extensive library of analytics that include free-text data sources, such as emails, instant messages and documents. We also target other sources, including structured data sources like trade and order data.

Among other things, our capabilities can be used to help identify key compliance risk factors and patterns indicative of rogue employee activities such as:

• Leakage of material non-public information that could lead to insider trading risks

• Misconduct, fraud risks or violations of company or regulatory policy

• Assistance with identifying the “flight risk” of key personnel to thwart defection to a competitor

• Bribery or corruption concerns that may put a company at risk under the FCPA, the UK Bribery Act or other country anti-bribery legislation

From a performance perspective, KYT Analytics Services can also identify positive activities in the communication patterns of successful employees so that these behaviours can be replicated throughout the firm. Our process can help identify leading actions by better understanding what leaders are doing: What are they saying? Whom are they mentoring? What are their patterns of research and information gathering? How can their successful communication patterns be replicated to others within the organisation?

3 | Know Your Trader (KYT) Analytics Services

KYT Analytics benefits

When combined with data visualisation tools and statistical analysis, KYT Analytics can be a powerful tool for management to identify anomalies that are only evident when taking into account the multidimensional attributes in the data, especially in the intersection of written communications and trading data.

Financial services clients are integrating KYT Analytics Services into their compliance activities to enhance their existing rules-based compliance tests and analytics. From a rogue trader or risk perspective, these existing rules-based queries and analytics — that often rely on the individual to “ask questions of the data” based on what is currently known — primarily focus on limited data sets, such as trade and order data. These rules-based tests often require both time and luck to uncover potential anomalies in the data. Unfortunately, most of the “don’t dos” and rules are known by perpetrators, who can circumvent them. This is where understanding the communication networks, in addition to the rules-based tests, can be important from management’s perspective.

KYT Analytics Services can help financial services companies increase their detection maturity by integrating customised analytics that incorporate text mining and communication patterns relevant to their risk profiles. When combined with data visualisation tools and statistical analysis, KYT Analytics can be a powerful tool for management to identify anomalies that are only evident when taking into account the multidimensional attributes in the data, especially in the intersection of written communications and trading data.

This approach can shift the focus to high-risk areas where controls are less reliable indicators of problems. Using KYT Analytics Services can also deliver other benefits, including:

Brand protection and reputational risk mitigation through innovative compliance and linguistic analysis techniques.

Competitive business intelligence is gained by benchmarking key attributes of “top performers” with respect to communication patterns, relationships and innovation.

Enabling management oversight through customised, easy-to-use reporting interfaces that aggregate large amounts of data to identify key risk areas or performance improvement opportunities.

Demonstrated commitment is conveyed by signaling to employees and outside stakeholders that management is serious about ethics and compliance.

Improved quality and risk mitigation is delivered through elevated controls, risk escalation methodologies and improved business processes that can reduce costs related to electronic discovery, regulatory inquiries and compliance-related activities.

4 Know Your Trader (KYT) Analytics Services |

In this screen capture, employee data was analysed by evaluating language related to individual pressure terms co-developed with the client, rogue trading risk terms and rationalization/justification terms to identify outlier employees. By analyzing the “term hit frequency,” the client can determine when all three events are occurring over time. Further drill-down analytics can be performed on select individuals and their respective communications, if desired.

In this screen capture, email communications were compared against multiple criteria to calculate an overall risk index. Risk criteria, co-developed with the client, included over a dozen objective filters, keyword tone, rogue trader high-risk keyword terms, email domain analysis, social network analysis, statistical anomaly detection and other customisable factors to identify high-risk communications or patterns on a per-employee ranking basis.

KYT Analytics Services examplesA leading global financial services firm integrated KYT Analytics Services into its overall compliance activity and targeted the following peer groups for communications review:

• Selected portfolio managers in higher-risk security products

• Selected regional and local brokerage branch managers

• Selected employees from a recent acquisition

• Selected global employees at risk for FCPA, bribery and corruption

In addition, KYT resources were allocated to support ad hoc internal investigations in support of human resource, legal, regulatory and internal affairs matters.

Below are illustrative reports and analytics developed for KYT review using sanitised data sources.

5 | Know Your Trader (KYT) Analytics Services

KYT Analytics Services sample tests

Analytics Description

Sentiment analysis

• Analysis of negative communications that mention other employees (angry, frustrated, secretive, derogatory, among other emotions) based on factual keyword terms and grammatical linguistic patterns that are agreed to with the client

Pecking-order analysis and social networking

• Relationship analysis and employee rankings that are derived from communication patterns such as forwards, CC only, reply rates and others

Mindshare

• Relative volume per topic is tracked as received or created by the employee

• Implied importance of topics is monitored for trending up or down over specific segment

Stressful topics

• Monitor and analysis of stressful communications associated with certain keyword topics and employees as co-developed with the client

• Comparative analysis of stressful topics and grammatical patterns among co-workers to help determine who appears more or less stressed by the topics

• Analysis of stressful communications by people or groups over determined time periods

Discussion Threads™ • Detection of individual instances concerning topics that attract unusual amounts of attention

Deletion analysis • Analysis that compares deletion patterns among employees related by classification, clearance, task, etc.

Alias clustering• Analytic that captures and links email electronic aliases for single

employees across multiple communication channels (e.g., [email protected] and other aliases)

Actor proximity

• A method that analyses the distance or closeness between co-workers as expressed in electronic communications (e.g., who emails who most frequently or not at all) to reveal and identify both informal and structured social networks

Actor centrality• Numeric ranking of centrality vis-à-vis a targeted group and determines

which employees are most frequently involved in the network, taking into account sending and receiving and job tasks

Keyword libraries

• Customised rogue trader and insider trading library of keyword terms leveraging EY’s library of over 3,000 keywords and augmented by linguists incorporating EY’s global experience and co-developed by the Association of Certified Fraud Examiners and EY’s computational linguists

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ContactsOur Fraud Investigation & Dispute Services team consists of professionals with a variety of skills and experience, which enables us to provide you with responsive solutions throughout Australia and New Zealand.

Analytics Description

Anomaly detection• Identifies communications that are statistically anomalous as compared

to other communications in the corpus of the data — by peer group or by employee

Concept clustering• Uses statistical text-mining algorithms to identify and list the top 1,000

to 10,000 key noun or noun-phrase concepts that may suggest unusual or high-risk terms being discussed in the data

Entity extraction

• Isolates and counts mentions of key individuals, geographic locations, company names, personally identifiable information (such as tax file numbers) and proper nouns, and maps them to employees, departments or other groups or individuals

Confidence intervals• Applies statistical confidence interval criteria to the larger population

or corpus of data to flag communications “most like” or similar to the sample set of high-risk documents

Oceania

Paul FontanotManaging PartnerMob: +61 447 464 [email protected]

Warren DunnPartner — Forensic Technology and Discovery ServicesMob: +61 411 755 [email protected]

With representation in local areas:

SydneyRob LockePartnerTel: +61 2 8295 [email protected]

BrisbaneTJ KoekemoerDirectorTel: +61 7 3011 [email protected]

Melbourne and AdelaideRoger Darvall-StevensPartnerTel: +61 3 9288 [email protected]

CanberraMatthew O’DonnellDirectorTel: +61 2 6267 [email protected]

PerthBrenton SteenkampPartnerTel: +61 8 9429 [email protected]

AucklandMatthew HammondSenior ManagerTel: +64 9 308 [email protected]

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© 2013 Ernst & Young, Australia.All Rights Reserved.

APAC No. AU00001748ED None

This communication provides general information which is current at the time of production. The information contained in this communication does not constitute advice and should not be relied on as such. Professional advice should be sought prior to any action being taken in reliance on any of the information. Ernst & Young disclaims all responsibility and liability (including, without limitation, for any direct or indirect or consequential costs, loss or damage or loss of profits) arising from anything done or omitted to be done by any party in reliance, whether wholly or partially, on any of the information. Any party that relies on the information does so at its own risk. Liability limited by a scheme approved under Professional Standards Legislation.

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