© 2016 IBM Corporation

Jeremy DoyleWatson Financial ServicesMay 24th, 2017

Delivering Unified Surveillance with IBM Surveillance Insights for Financial Services Surveillance

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Agenda

Industry Perspective

Introducing Surveillance Insights

Voice Surveillance

Closing Thoughts

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Key Takeaways

1. Behaviour and Risk Profiling

Behaviour analytics is a critical component of any future surveillance solution moving forward. It is the only way as an industry we can truly realise Unified Surveillance.

2. Machine Learning

ML needs to be at the heart of your surveillance technology platform. Supervised learning will significantly reduce false positives and ensure adaptive risk model for ever increasing complexities of risk. If cognitive solutions are deployed correctly, it will be an asset that apricates value over time, rather than decline like current rules based systems

3. Collaboration

As principles of open API economy and cloud become more established within the Financial Services sector, we will see tight collaboration between banks to solve the current challenges and costs associated with risk and compliance.

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Three capabilities differentiate cognitive systems from traditional programmed computing systems…

ReasoningTheyreason.Theyunderstandunderlyingideasandconcepts.Theyformhypothesis.Theyinferandextractconcepts.

LearningTheyneverstoplearninggettingmorevaluablewithtime.Advancingwitheachnewpieceofinformation,interaction,andoutcome.Theydevelop“expertise”.Understanding

Cognitivesystemsunderstandlikehumansdo.

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What do we mean when we discuss Surveillance?

Elder FraudClient

Suitability

Conduct Risk

Sales Practices

Market Abuse

Complaints

CollusionInsiderTrading…

Pump&DumpFrontRunning…

Miss-sellingMiss-representation….

SalesMalpractice….

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Opportunity to Transform Surveillance with Cognitive

Go Beyond Rules Take Holistic Approach

Leverage behaviours and machine learning toproactively identify abnormalities and potential

misconduct without pre-defined rules

Integrated analytics, focused on total conduct across activities and channels

Machine LearningbehaviourProactive

ActivityE-comms

VoiceTrade

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Surveillance Insight for Financial Services

Fuse insights to detect suspicious activities

View linkages with instant drill-down & playbacks

Build employee profiles with personality & behaviour traits

See alerts & investigationsfrom continuously updated risk models

OrderTrade

ExecutionReference

NewsSocial

EmailChat

Voice

Reduced cost of employee non-compliance & misconduct

Faster detection of sophisticated scenarios

Risk based prioritization of alerts and reduced false

positives

Transactions

Communications

External

Surveillance

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Case Study: A Proven Foundation of Uncovering Misconduct

Accurate Results

Further Expansion

Innovative Technology

First run of the system without knowledge of the scenarios resulted in:

36 tests detecting threats within the top 3% out of a database of 5,500 profiles

IBM expanded into additional industries as incidents of misconduct increased in the headlines:

• WikiLeaks• Snowden• Texas Killings

A partnership was created between DARPA and IBM to build a cognitive Insider Threat Solution to identify serious national threats. IBM has continued to develop this asset, creating Surveillance Insight for Financial Services

which helps customers better uncover misconduct

3 Main Models

• Fraud

• Espionage

• Sabotage

DARPADefense Advanced

Research Projects Agency, an agency of the U.S.

Department of Defense

Challenge

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Use case: Identifying collusion for market manipulation

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Motivation

CommunicationTrading

Risk

-Communication Event Proximity

Email

Voice

ChateComm

Anomalous Language

Repetitive Language

Voice

Offline Conversation

Cross Conversation

• Detecting collusion is highly complex.

• It requires information from multiple sources – trading, ecomms, voice, and others such as HR system.

• It requires a model that can remember new patterns of behaviour and connections and ‘self-learn’ (supervised)

• First Identify higher level risk indicators – “Trader Motivation”, “Communication Risk”, “Trading Risk and apply inference model to identify overall “Collusion Risk”:

• Communication Risk indicators eg. Repetitive language• Event proximity indicator – requires call meta data to be correlated with the alert proximity• Know Your Trader indicators – anomalies compared to the norm, • Voice anomaly indicators – requires identification offline conversations, conversations across

multiple voice channels such as turret, desk phone and mobile

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CaseStudy:RecentsuccessataTier1Bank

Modernize the communications archiving and adopt an open and flexible architecture

Consolidate and manage the supervision and surveillance of all communications and transactions

Improve market abuse detection capabilities

Replace the incumbent regulatory compliant archiving infrastructure

Enhance supervision and surveillance

Support the bank’s holistic surveillance strategy

Challenge

Phase 1 Phase 2 Phase 3

Highlights of the IBM Solution • IBM GBS services (Strategy Formulation)• Partnership with Actiance Alcatraz (Regulatory Compliant Archiving & Supervision)• IBM Surveillance Insights (Advanced Feature Extraction + Holistic Surveillance)• Entire Solution offered as SaaS on IBM SoftLayer Infrastructure

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Challenges of Integration with voice archives

*Quote Source: http://www.legaltechnews.com/id=1202752478714/-Putting-More-Ears-to-the-Ground-The-Rise-and-Challenges-of-Audio-Analytics-#ixzz43CC90IT3

Currentaudiorecordingsystemsweredesignedtocaptureandstoredataandlistentoitfromaplaybackperspectivebutlargescaleretrievalwasn’tenvisionedwhenalotofthesesystems

werecreated.*

Audioisstoredinproprietaryformats

Audioisduplicatedsothatitcanbeanalyzed

Buildingconnectorstoextractaudioforanalyticsraisesconcernoverrobustness(i.e.haveallthecallsbeenindexed?)

Limitedbulkdownloadcapabilities

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2

3

4“ “

Global Head of Legal Discovery Operations, Top 3 European Bank

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Surveillance Insights for Voice

Speech to Text

Language Analysis Tone

Analyzer

Trader Phone Calls

FLAC,PCM, WAV, Ogg, or Raw VoIP Packets

Language Translation

Complimentary Services

Converts human voice into written

word by leveraging machine to combine

information on grammar and

language structure with knowledge of the composition of

the audio signal

Natural language processing and

machine learning algorithms extract

semantic meta-data from content (i.e. people, places,

companies, facts, languages)

Linguistic analysis to detect three types of

tones from text: emotion, social tendencies, and language style

The streaming solution can invoke existing services or external services to extract

relevant information

Provides domain-specific translation in multiple languages, utilizing Statistical

Machine Translation techniques that have been perfected in our

research labs

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Case Study: Recent eComm success at a Tier 1 Bank

Phase 1 Phase 2 Phase 3

Replace the incumbent regulatory compliant archiving

infrastructure

Enhance supervision and

surveillance

Support the bank’s holistic

surveillance strategy

Challenge

IBM Solution:• IBM Strategy Formulation &

Business Case• Partnership with Actiance

Alcatraz (Regulatory Compliant Archiving & Supervision)

• IBM Surveillance Insight (Holistic Surveillance and Advanced Feature Extraction)

• SaaS on IBM SoftLayer Infrastructure

A Tier 1 Bank was looking to modernize its communications archive and adopt an open and flexible architecture.It needed a solution to consolidate and manage the supervision and surveillance of all communications

and transactions and improve the firm’s market abuse detection capabilities

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Closing Thoughts - Transforming Surveillance using Cognitive

• Separating meaningful data from noise and the sub-optimized classification of data to reduce false positives.

• Easily navigate through large volumes of communications: Trades/Transactions, Electronic Communications, Voice, Activity using advanced graph analytics and machine learning.

• Sophisticated behavioural analysis to build employee conduct risk profiles in order to identify outlining risks missed by traditional rules bases solutions.

• Unique Voice Surveillance capabilities, delivering highest Word Accuracy Rate output.

• Holistic Surveillance platform for a future proof solutions for the ever changing complexities of Conduct Risk.