Leveraging Technology in the Battle against Financial Fraud

Report
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?
3
Sure, you’ve heard about Bernie and Jerome…
4
… but can you pick out the fraudster here?
A
B
C
Amy Lynette Sanders
Grand Rapids, Michigan
Ray Van Norman
Omaha, Nebraska
Jane Wolff
Yarmouth, Massachusetts
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.
.
Branch Manager.
Transferred funds from
customer accounts into
her own – for over 3½
years.
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
Sources:
KPMG, Celent, ABA, Tower Group, Javelin Research, CIMIP
6
Is Fraud A Trillion Dollar Problem Globally?
Banking
$20B
Healthcare
$125B
Brokerage/Securities
$150B
Mortgage
$10B
Insurance
$100B
Retail
$42B
Telecom
$55B
$502 billion
US fraud losses
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
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
Top 5 fraud threats (2012)
Card Fraud
Check Fraud
Phishing and Vishing
ACH and Wire Fraud
ATM Fraud
0
10
20
30
40
50
60
70
80
90
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”
© Memento, Inc. 2010 – All Rights Reserved
10
Losses continue to grow: SAR by the numbers
SAR Volume
800,000
732,563
700,000
697,389
SARs Submitted
Total: 5,549,559
600,000
500,000
411,697
400,000
Check Fraud: 1,141,498
Money Laundering:
3,013,569
300,000
200,000
100,000
52,069
152,874
21,655
14,385
115,757
0
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Total SAR Volume
check
Money Laundering
%of total SARs for check and ML: range 69.2 - 78.3
Avg. 74.4
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THROUGH THE LENS OF A
FINANCIAL INSTITUTION
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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
13
How do banks respond?
“Keep the bad “Stop them from
guys out”
stealing”
“Break the
cycle”
• IT/network security
• Transaction monitoring
• Investigate cases
• Online authentication
• Employee monitoring
• Prosecute criminals
• Applicant screening
• List checking
• Report to FINCen
Focused on
protecting the
perimeter
Focused on
protecting customer
accounts
Focused on
preventing future
attacks
TowerGroup estimates that for each $1 spent on fraud management, fraud
losses will be reduced by $8
Implement comprehensive approach across all
channels and products
Deposit Account
Check
ACH
Branch
Deposit
Call Center
Kiting
ATM
On-Us
Online
(incl. ACH Conversions)
(Origination)
Wire
Debit
14
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
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FFIEC compliance – Layered security
Layer 5
Entity Link
Analysis
• Enables analysis of relationships among
internal and external entities and their
attributes (e.g., users, accounts,
machines)
Layer 4
User / Acct. Centric
Multi Channel &
Product
• Monitors and analyzes user and account
behavior across channels, and
correlates alerts across channels and
products
User / Acct. Centric
Specific Channel
• Monitors and analyzes user and account
behavior, and identifies anomalous
behavior using rules or statistical
models
Layer 3
Layer 2
Layer 1
Navigation Centric
Endpoint Centric
Source: Gartner
© Memento, Inc. 2012 – All Rights Reserved
• Analyzes session behavior and points
out anomalies
• Analyzes mobile device location
• Secure browsing, OOB authentication
and transaction verification
• Endpoint device identification, location
data
17
HOW CAN
TECHNOLOGY HELP?
Enterprise Fraud Management Systems
Case Management
Workflow and reporting
Alerts and incidents
Proactive Monitoring &
Analytics
Identify suspicious behavior
Business user control
Forensic Research &
Investigations
Queries and analysis
Collaborative research
Data Aggregation & Management
Multiple sources
Different data types
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Enterprise Fraud Management Data
Customer Data
Employee Data
Name, address, phone,
email …
name, ID, branch, job code,
contact info …
Account Data
Transaction Data
Status, open date, balance
…
check, deposits, ACH, wire,
other debits, RDI, returns …
Maintenance/Inquiry Data
contact info changes, service
changes, balance lookups …
3rd Party Lists
black lists, white lists, OFAC
…
Analytics Output
profiles, risk scores, alerts …
Other Detection Systems
alerts , other data as
required…
• Single enterprise
data store for
financial crime and
ops risk mgt
• Rich repository of
cross-channel
transaction &
reference data
• Source system
agnostic
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Multiple Approaches to Fraud Analytics
Patterns/Rules
Profiling
Adaptive Analytics
Link Analysis
• Advanced business rules and
statistical techniques
• Contextual history of customer,
employee and peer group behavior
• Fraud is discovered through a
combination of risk indicators
• Uncover risky relationships between
people, accounts, alerts, etc.
Example: Employee Fraud Detection
Fraud Type
Example 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
Example: ACH Fraud Detection
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
Customer and Account Profile
Transaction Details
Customer and Account Data
Name, address, phone, acct status, daily balance…
Originator Information
Contact details, funding account, …
+
Maintenance / Inquiry Activity
Address or service changes, balance lookups …
ACH Activity
Historical activity across all channels
•
•
•
•
•
•
•
•
Amount
Timing
Receivers
Type
Channels
Credits
Debits
Routing
Statistically-driven risk score for every transaction
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Example: Check Fraud Detection
Multi-dimensional pattern analysis
Check serial number sequences
• Book detection, distance out of
sequence
Velocity
• Amounts
Acct
Intimacy
Serial #
Acct
Profile
• Quasi-periodic amounts, non-quasi
periodic amounts
• Likely amounts, intimate amounts
• Velocity analysis
• Account velocity (balances), book
Multiple
checkboo
ks
Timing
$
Amount
velocity
• Account relationships
24
NEW TECHNOLOGIES
Emerging and enabling technologies
• Big Data
• Cloud Computing
• Mobile
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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
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
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, personto-person payments, and substitution of mobile device for credit
card, debit card or checks
29
Who Consumers Trust with Mobile Payments
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Evolving payment landscape
WRAP UP
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
Fraud management
is a collaboration
© Memento, Inc. 2012 – All Rights Reserved

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