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LEVERAGING TECHNOLOGY IN THE BATTLE AGAINST FINANCIAL FRAUD Maria Loughlin April, 2012 © Memento, Inc. 2011 – All Rights Reserved.

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Presentation on theme: "LEVERAGING TECHNOLOGY IN THE BATTLE AGAINST FINANCIAL FRAUD Maria Loughlin April, 2012 © Memento, Inc. 2011 – All Rights Reserved."— Presentation transcript:

1 LEVERAGING TECHNOLOGY IN THE BATTLE AGAINST FINANCIAL FRAUD Maria Loughlin April, 2012 © Memento, Inc. 2011 – All Rights Reserved

2 Exploring fraud and fraud management Through the lens of a Financial Institution (FI) What are the threats, emerging channels and evolving risks? How to respond? Through the lens of a technologist How can technology help? What lies ahead? 2

3 Sure, you’ve heard about Bernie and Jerome… 3

4 … but can you pick out the fraudster here? 4 Amy Lynette Sanders Grand Rapids, Michigan Ray Van Norman Omaha, Nebraska Jane Wolff Yarmouth, Massachusetts Branch Manager. Transferred funds from customer accounts into her own – for over 3½ years. Chairman and CEO. Stole $5.7 million by creating fictitious lines of credit over a 10-year period. Husband and wife pair Benjamin Wolff (79) and Jane (72) wrote fraudulent checks for hotels, inns, and stores in Concord, Newburyport, Rockport, and Andover.. ABC

5 Sobering bank fraud statistics As much as 35% of operational loss in financial services is fraud – that’s $20B annually A mid-size US bank loses $50M to check fraud annually A top 10 credit card issuer loses $100-400M to first party credit card fraud annually 60% of bank fraud involves an insider Identity theft cost the US $48B in 2008 40% of ID theft is committed by collusive criminal networks 5 Sources: KPMG, Celent, ABA, Tower Group, Javelin Research, CIMIP

6 Is Fraud A Trillion Dollar Problem Globally? Banking Healthcare Brokerage/Securities Mortgage Insurance Retail Telecom $20B $125B $150B $10B $42B $100B $55B Sources: TowerGroup, Stanford Law School, Cornerstone Research, The Prieston Group, U.S. Dept. of Health & Human Services, U.S. Dept. of Justice, National Retail Federation, FIINA $502 billion US fraud losses 6

7 Why does bank fraud continue to be a problem? New products and channels expose new schemes Defenses usually come long after new schemes are hatched Fraud is a business Highly leveraged schemes Increased role of organized crime Weak defenses Low efficiency, increasing cost Complex problem, disconnected data and systems, limited innovation Failure to comprehensively monitor accounts, account touch points

8 Top 5 fraud threats (2012) Source: 2012 Faces of Fraud survey Sponsored by Authentify, Guardian Analytics, i2, RSA Security, Wolters Kluwer Financial Svcs

9 Payments trends that affect fraud Emerging technologies and rapid innovation Increase in # of players involved in the payments supply chain Increase in # of payment options for consumers Shift from Credit/Debit to ACH via Payment Services Evolving fraud Cross channel fraud International organized crime rings Increased speed of use from compromise to fraud Shift in target From mega data breaches to smaller merchants Filtering down to rural areas Changing consumer views More open to alternative payments More conscious of security, yet willing to share personal information with “friends” 9

10 Losses continue to grow: SAR by the numbers © Memento, Inc. 2010 – All Rights Reserved 10 %of total SARs for check and ML: range 69.2 - 78.3 Avg. 74.4 SARs Submitted Total: 5,549,559 Check Fraud: 1,141,498 Money Laundering: 3,013,569


12 Why do banks care about fraud? Fraud losses go straight to the bottom line Perceptions of insecurity leads to Reputational risk Customer retention challenges Operational expense Regulatory oversight/fines Calls for more regulation 12

13 How do banks respond? “Keep the bad guys out” IT/network security Online authentication Applicant screening Focused on protecting the perimeter “Stop them from stealing” Transaction monitoring Employee monitoring List checking Focused on protecting customer accounts 13 “Break the cycle” Investigate cases Prosecute criminals Report to FINCen Focused on preventing future attacks TowerGroup estimates that for each $1 spent on fraud management, fraud losses will be reduced by $8

14 Implement comprehensive approach across all channels and products 14 Deposit Account Online ATM Call Center Branch Check ACH (Origination) ACH (Origination) Wire Debit On-Us ( incl. ACH Conversions) Kiting Deposit

15 Regulation also drives FI action Layered Security FFIEC Guidance 2005: The Federal Financial Institutions Examination Council (FFIEC) issued guidance to banks on standards for Internet banking 2007: Banks responsible for compliance Of 200+ respondents: 58% say their institutions will increase fraud spend in 2012 Only 11% believe the guidance will significantly reduce fraud

16 User / Acct. Centric Specific Channel Monitors and analyzes user and account behavior, and identifies anomalous behavior using rules or statistical models Layer 3 Navigation Centric Layer 2 Analyzes session behavior and points out anomalies Analyzes mobile device location Layer 1 Secure browsing, OOB authentication and transaction verification Endpoint device identification, location data Endpoint Centric User / Acct. Centric Multi Channel & Product Layer 4 Monitors and analyzes user and account behavior across channels, and correlates alerts across channels and products Entity Link Analysis Layer 5 Enables analysis of relationships among internal and external entities and their attributes (e.g., users, accounts, machines) FFIEC compliance – Layered security © Memento, Inc. 2012 – All Rights Reserved 16 Source: Gartner


18 Enterprise Fraud Management Systems 18 Data Aggregation & Management Multiple sources Different data types Data Aggregation & Management Multiple sources Different data types Proactive Monitoring & Analytics Identify suspicious behavior Business user control Proactive Monitoring & Analytics Identify suspicious behavior Business user control Forensic Research & Investigations Queries and analysis Collaborative research Forensic Research & Investigations Queries and analysis Collaborative research Case Management Workflow and reporting Alerts and incidents Case Management Workflow and reporting Alerts and incidents

19 Enterprise Fraud Management Data 19 Analytics Output profiles, risk scores, alerts … Customer Data Name, address, phone, email … Account Data Status, open date, balance … Employee Data name, ID, branch, job code, contact info … 3 rd Party Lists black lists, white lists, OFAC … Transaction Data check, deposits, ACH, wire, other debits, RDI, returns … Single enterprise data store for financial crime and ops risk mgt Rich repository of cross-channel transaction & reference data Source system agnostic Maintenance/Inquiry Data contact info changes, service changes, balance lookups … Other Detection Systems alerts, other data as required…

20 Multiple Approaches to Fraud Analytics 20 Patterns/Rules Advanced business rules and statistical techniques Profiling Contextual history of customer, employee and peer group behavior Adaptive Analytics Fraud is discovered through a combination of risk indicators Link Analysis Uncover risky relationships between people, accounts, alerts, etc.

21 Example: Employee Fraud Detection Fraud TypeExample Scenarios Theft from institution Self-dealing (e.g., fee reversals increasing overdraft limits) Inappropriate account maintenance on own or close associate account (e.g. check hold policy override) Incentive compensation schemes GL theft (debit to cash offset to employee acct) Theft from customer Debits from dormant, elder, out-of-region, high net worth accts Inappropriate acct maintenance (e.g., changing phone #, email, address); followed by unauthorized or unusual transactions Inappropriate acct inquiries, often out-of-region or business unit Inappropriate access to reports Screen capture, print screen

22 Example: ACH Fraud Detection 22 Transaction Details Amount Timing Receivers Type Channels Credits Debits Routing + Combine Advanced Analytics and Business Rules Fraud Indicators: Unusual access (IP, device ID, time of day, etc.), account maintenance, fund consolidation, negative balance, unusual amount, routing, timing, known bad receiver Business Rules: White/black lists, institution defined rules Statistically-driven risk score for every transaction ACH Activity Historical activity across all channels Customer and Account Profile Maintenance / Inquiry Activity Address or service changes, balance lookups … Customer and Account Data Name, address, phone, acct status, daily balance… Originator Information Contact details, funding account, …

23 Example: Check Fraud Detection Check serial number sequences Book detection, distance out of sequence Amounts Quasi-periodic amounts, non-quasi periodic amounts Likely amounts, intimate amounts Velocity analysis Account velocity (balances), book velocity Account relationships 23 Serial # Velocity Multiple checkboo ks Timing Acct Profile $ Amount Acct Intimacy Multi-dimensional pattern analysis


25 Emerging and enabling technologies Big Data Cloud Computing Mobile

26 Cloud computing Reduced costs Some aspects of payments are moving to the cloud Risks: Assuring proper data protection and compliance with security and privacy regulations Inadequate controls at third party service providers Authentication and reliance on passwords 26

27 The mobile revolution Nearly half (46%) of American adults are smartphone owners as of February 2012, an increase of 11% over last May Source: Pew Research Center’s Internet & American Life Project, March 2012 Use of mobile banking expected to grow rapidly: expanding to 38M households by 2015 Source: FDIC Supervisory Insights - Winter 2011 27

28 Mobile financial services 4 usage patterns expected: Mobile Banking – Mobilization of existing online capabilities (e.g., balance checks, transfers of funds between customer accounts, bill payment to pre-authorized recipients) Alerting – Providing a convenient channel to alert customers of account activity Services Replacement – Replacement of select services that require physical customer presence (e.g., remote deposit capture) Mobile Payments – Including contactless payments, person- to-person payments, and substitution of mobile device for credit card, debit card or checks 28

29 Who Consumers Trust with Mobile Payments 29

30 Evolving payment landscape 30


32 Parting words… Fraud attempts and fraud losses continue to grow. Yet, there is opportunity to fight back harder and smarter. Customer education New tools and new technologies Information protection Fraud detection and management Increased collaboration Engage customers in fraud management Share information across banks Collaborate with regulators, government, employees and third parties

33 © Memento, Inc. 2012 – All Rights Reserved Fraud management is a collaboration

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