More than a Numbers Game
Building Better Strategies that Leverage Unique
Kinds of Data
Dennis D’Ambrosio
Senior Fraud Operations
Analyst
KeyBank
Michael Holloway
Senior Fraud Operations
Analyst
KeyBank
© 2014 Fair Isaac Corporation. Confidential.
This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent.
Lamar Shahbazian
Sr. Director
FICO
Congratulations!
Bank: Hello, this is your bank. The check you deposited is
counterfeit and your account is now overdrawn $2,400.
It can’t be, I won the Clearing house sweepstake.
Image Source: http://www.bellasavvy.net/archives/49380
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© 2014 Fair Isaac Corporation. Confidential.
Check Fraud
Despite declining check usage, check fraud is still ever present
Source of Check Fraud Losses
Trend in Noncash Payments
Checks
Percentage of Total Losses
Debit
Counterfeits
50
Forgeries
75
45
40
% of Total Losses
Billions
35
30
25
20
15
10
50
25
5
0
0
2000
2003
2006
2009
2012
1Q06
1Q07
1Q08
1Q09
1Q10
1Q11
The 2013 Federal Reserve Payment Study.
*RDIs include NSFs, closed accounts, refer to maker, stop payments, uncollected funds, remotely created checks, no account
found, government reclamations, and other return loss reasons.
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© 2014 Fair Isaac Corporation. Confidential.
1Q12
1Q13
Check Printing Past and Present
Past
► MICR
Ink required
► Limited
4
check printing resources
© 2014 Fair Isaac Corporation. Confidential.
Present
► Print
anywhere
► Image
exchange networks
► Mobile
Deposit
Check Detection Past and Present
► Past
► Feel
the paper
► Look for the perforation
► Look for discoloration
► Hold it up to the light
► Present
► No
Challenges…
Paper to handle
► Black & white images
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© 2014 Fair Isaac Corporation. Confidential.
Image Analysis
► Image
Fraud Detection
► Takes
check fraud detection beyond the
MICR line
► Signature and check stock analysis
Address
Payee
Signature characteristics are extracted,
weighed and compared using a neural
network and fuzzy logic.
Crossings
Curves and
Loops
General design
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© 2014 Fair Isaac Corporation. Confidential.
MICR Data
Upstrokes
Enclosed
Areas
Data Elements
► Signatures
and check stocks are digitized and scored
► ASV
Result Codes = analysis outcomes: Signature OK, different, new, etc
► ASV Match Rates: 0–100 confidence score
► APIA Result Codes = analysis outcomes: OK, validation failed, new, etc
► APIA Match Rates: 0–100 confidence score
ASV RESULT
10
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© 2014 Fair Isaac Corporation. Confidential.
ASV MATCHRATE
00
APIA RESULT
15
APIA MATCHRATE
08
Strategy Design
Why Use Decision Trees?
► Run
large volumes of data and “find the
nuggets”
► Implement
existing rules
► Profiling
fraud against non-fraud allowed us
to look for improvement
► Visual
► Easy
8
to explain
© 2014 Fair Isaac Corporation. Confidential.
Strategy Design
Decision Trees Help Verify and Suggest Potential Improvements
► Image
analysis output = result codes and
match rate scores
► Rules
drive alerts based on scores,
account type, transaction data
► Strategy
Trees validate rules and
performance
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© 2014 Fair Isaac Corporation. Confidential.
What’s Next?
► System
► New
10
Upgrade—new analysis engine and risk indicators
Strategy Design
© 2014 Fair Isaac Corporation. Confidential.
Wire Fraud
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© 2014 Fair Isaac Corporation. Confidential.
Wire Fraud
“Wire Fraud is difficult to
detect; comes in many
different colors and flavors.”
David Pollino
Senior Vice Presitdent
Enterprise Fraud Prevention Officer
at Bank of the West
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© 2014 Fair Isaac Corporation. Confidential.
Wire Transfer Fraud Detection
► KeyBank
implemented enterprise fraud
detection application 2011
► Moved
from static rules to behavioral based
application
► Over-compensated by implementing
additional rules
► And
the result was…
Image from: www.obviouslyopinionated.com
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© 2014 Fair Isaac Corporation. Confidential.
Detection and Volume Challenges
White-boarded rules
► White-boarded
rules to eliminate
unnecessary alerts from Q2 2012
► Improvement
but monthly volume
was still too high
Alerts
Goal: Continue to reduce alerts while
maintaining frauds identified
Frauds
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© 2014 Fair Isaac Corporation. Confidential.
Looking for Needle in a Stack of Haystacks
Less than 50 Frauds out of 960,000 Transactions
► Decided
to pursue more extensive rule analysis
using decision trees
► Built
a transaction file of frauds and non-frauds
► Initially
met via webex, then opted to have two
day “bootcamp”
► Interactively
dissected ‘pockets’ of fraud
► Constructed
several rule-set options in a
few hours
► Learning:
Risks unique to specific channels
became evident
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© 2014 Fair Isaac Corporation. Confidential.
Balancing Volume with Quality of Alerts
► Implemented
new rules in Q3 and
Q4 2013
► Reduced
alerts created by 39%
Q3 over Q2, further reduced alerts
by 45% Q4 over Q3 2013
Alerts
► Fine
tuning in 2014 has continued
to reduce alerts and increase
detection rates
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© 2014 Fair Isaac Corporation. Confidential.
Frauds
Stellar Results
While alerts went down, averted losses went up
► New
rules led to richer alerts for
operations team
► Majority
of all frauds were
detected
► Ongoing
analysis for continued
optimization
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© 2014 Fair Isaac Corporation. Confidential.
Alerts
Averted
Next Steps
► Continue
to evaluate rule effectiveness of rules on an
ongoing basis
► Most
recent rule project leveraging
FICO® Analytic Modeler Decision Trees Professional
software is for Mobile Deposit Fraud detection
► Card
18
rules on-deck
© 2014 Fair Isaac Corporation. Confidential.
Conclusion
► FICO’s
analytic tools have transformed our fraud detection methodology; we use data to
drive insights and empirically based decisions
► Our
operations teams have a greater confidence in alerts; our rules look at several factors
such as customer segment, channel, business logic in addition to score
► This
19
approach has yielded improved false positive rates and a reduction in fraud losses
© 2014 Fair Isaac Corporation. Confidential.
Thank You!
Dennis D’Ambrosio
Michael Holloway
Lamar Shahbazian
dennis_d'ambrosio@keybank.com
michael_w_holloway@keybank.com
lshahbazian@fico.com
© 2014 Fair Isaac Corporation. Confidential.
This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent.
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© 2014 Fair Isaac Corporation. Confidential.
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Dennis D’Ambrosio
dennis_d'ambrosio@keybank.com
22
© 2014 Fair Isaac Corporation. Confidential.
Michael Holloway
michael_w_holloway@keybank.com
Lamar Shahbazian
lshahbazian@fico.com