catching bust-out fraud

Catching Bust-Out FraudTo stop the criminals, find the connections

©2014 Fair Isaac Corporation. All rights reserved. 2

Sonia and Francesca are both applying for credit cards

Both applicants appear the same. They have similar profiles and personal characteristics. Yet Sonia is connected to other members of a criminal fraud network that is launching a bust-out fraud scheme.

By the time it’s clear that one of these applicants is a good customer and the other is a criminal it may be too late to stop huge losses.

Sonia Francesca


And the risk is growing…

Here’s an example of how massive and sophisticated bust-out fraud can be

>$200M In losses

Clear out all accounts and suddenly disappear

25,000 Fraudulent cards

Create accounts and credit lines

1,800 Drop addresses

Use a variety of locations to receive mail

50 Complicit businesses

Make purchases and build credit balances

7,000 Synthetic identities

Steal or acquire valid identity information

18,000 Individuals

Organized fraudsters and insiders


Fraudsters like Sonia are dipping into an ocean of opportunity

With today’s instant transactions and growing online and mobile channels, there are many ways to perpetrate and disguise bust-out fraud schemes.

Already such schemes account for

10–15% of banks’ unsecured bad debt, amounting to tens of billions in losses a year


Will the bank be able to spot Sonia’s scheme and stop it before losses mount?

Perpetrators look like normal customers

Applicants generally use valid identity information (stolen or acquired) to apply for the credit.

If fraud systems look only at individual applicants, they probably won’t see anything wrong.

Their schemes cross product lines and geographies

Fraudsters keep accounts current while increasing credit limits and applying for additional cards and credit lines.

If fraud systems are focused on lines of business, they probably won’t be able to detect this cross-channel fraud.

At the moment of bust-out, they execute very fast

Once fraudsters reach a target amount of credit or time, they rapidly increase spending and build balances.

Because escalation usually occurs over just a day or two—bank systems probably won’t react in time to stop it.


YES, the bank can stop Sonia by using social network analysis. This analytic technique detects bust-out fraud schemes before the chain of events leading to big losses can unfold.

How? By going after the fraud ring’s greatest vulnerability…


Sonia’s fraud ring is vulnerable because, like other criminal networks, it reuses identity informationTo pass verification checks and regulation, Sonia uses synthetic identities combining real and fake information. She varies spelling and makes other small changes.

Social network analysis matches the various permutations across data sources to link and identify a single individual related to risk.

Cards

Sonia A. Smith1 Edison RdBedford Park SA 5042T: 08 8177 0035LIC: 1702188364DOB: 07/09/84

DDA/CA

A. Sonia Smith1067 6th AveBedford SA 01510T: 08 8356 4131LIC: 1702188364DOB: 07/09/84

Bad Guys

Sonia Carr-Smith1 Wallace AveBedford SA 1510T: 06 8177 0035LIC: 17-OUYRE-+8364DOB: 07/08/84

Employees

Sonia A. CarrOne Edison RdBelfort SA 1510T: +64 8 8177 0035LIC: 7102188364


Next link analysis matches Sonia’s information with that of other individuals to reveal the fraud ring.Because creating and maintaining identities involves effort and expense, fraud rings usually recycle bits and pieces among members.

Address:One Edison RoadCherry Hill, NJ 08034

Telephone:908-555-1234

John Benton

Bad List

Charge Off Credit Cards

Charge off loan

Jordana Mack

Jordan Mako

Investigator mortgage fraud

Email: [email protected]

Sonia A. Smith

License Number: 1543987223@


Social Risk Scoring and Triage

Social LInk Visualization

Alert Processing

ActActs, via automated alerts and rules-driven triage to focus investigator attention on highest risk cases

5 AnalyzeAnalyzes networks for patterns indicative of fraud rings

4 LinkLink entities into networks via shared or similar attributes (names, phone numbers, etc.)

3 MatchMatches attributes to create a single view of entities (people, places, things)

2

� Customer Data

� Employee

� SARS

� Case Management

� Third-Party LexisNexis CFAC

� Vendor

� Applicants

SearchSearches across disparate internal and external sources

1

FICO® Identity Resolution EngineThe process that reveals Sonia’s network and stops the bust-out fraud scheme


� Customer Data

� Employee

� SARS

� Case Management


� Vendor

� Applicants


1


Because bust-out schemes may involve more than one product, business line and geography, FICO® Identity Resolution Engine glides across multiple sources, examining data where it is, as it is (without extraction, cleansing normalization), piecing together relevant bits into the bigger picture, while complying with privacy regulations and requirements.

This “federated data search” can take place in batch or in real time as credit applications and transactions stream in.


MatchMatches attributes to create a single view of entities (people, places, things)

2

� Customer Data

� Employee

� SARS

� Case Management


� Vendor

� Applicants


1


To determine who is really whom, FICO® Identity Resolution Engine recognizes attribute relationships that are similar enough to be a match, though not exact. This step, called “entity resolution,” requires seeing through the inaccuracies and formatting peculiarities of the numerous data sources to recognize that the same entity is being described.


LinkLink entities into networks via shared or similar attributes (names, phone numbers, etc.)

3 MatchMatches attributes to create a single view of entities (people, places, things)

2

� Customer Data

� Employee

� SARS

� Case Management


� Vendor

� Applicants


1


This step identifies who shares attribute data. As FICO® Identity Resolution Engine uncovers shared data, a network of connections emerges. Links between individuals who have no attribute data in common, but are connected to other people who do, are also revealed.




Alert Processing


5 AnalyzeAnalyzes networks for patterns indicative of fraud rings

4


FICO® Identity Resolution Engine determines the level of fraud risk represented by a network of connections, quanitifying it in the form of a score. Some factors that raise fraud risk scores include:

� Links with known fraudsters in a bank’s fraud or anti-money laundering (AML) databases

� Links with bank insiders (a large percentage of bust-out fraud is facilitated by employees)

� Unusually large networks with many customers and accounts (indicative of a growing scheme ready to bust out)




Alert Processing


5


FICO® Identity Resolution Engine can generate alerts in real time as data from incoming credit applications is analyzed. Thresholds and rules can be set up to automatically refer applications scoring above a certain threshold to an investigator. Scoring also enables cases to be prioritized within queues.

Visualization tools help investigators quickly comprehend and explore the network of connections to judge the nature and extent of the threat.


Moral of the story: The sooner you can recognize fraudsters, the better you can protect your customers and institution from organized criminals

Some FICO client results:A bank that added social network analysis to its existing rules-based fraud detection improved performance by.............

Another, adding it to analytics-based detection, achieved an additional....................

50%30%


Francesca

These two consumers are applying for a credit card.

One of them will become a profitable customer for years to come. The other will try to steal millions.

Tell the difference sooner.

Sonia

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FICO is a trademark or registered trademark of Fair Isaac Corporation in the United States and in other countries. Other product and company names herein may be trademarks of their respective owners. © 2014 Fair Isaac Corporation. All rights reserved.

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Stop bust-out fraudNow the very networks fraud rings use to perpeturate their crimes become their downfall

Learn more:Download the white paper on this topic:

Uncovering Bust-Out Fraud with FICO® Identity Resolution EngineCheck out our blog:

Banking Analytics Blog

http://bankinganalyticsblog.fico.com

http://www.fico.com/en/wp-content/secure_upload//Uncovering_Bust_Out_Fraud_with_FICO_Identity_Resolution_Engine_3004WP.pdf

http://www.fico.com/en/wp-content/secure_upload//Uncovering_Bust_Out_Fraud_with_FICO_Identity_Resolution_Engine_3004WP.pdf

http://bankinganalyticsblog.fico.com

catching bust-out fraud

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crosschannel fraud