Bustout Fraud: Catch it fast with advanced analytics

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1 Bustout Fraud: Catch it fast with advanced analytics

2 2 The longer it takes to identify bustout fraud, the more you lose. That s where we come in Tough times are a challenge in more ways than one. Lenders, for instance, usually see increases in bustout fraud, also often referred to as first party fraud. Perpetrators apply for credit using many elements of their real identities, so their applications are not caught by traditional application fraud models. In addition, there are multiple, complex patterns by which bustouts develop after accounts are booked. Part of perpetrators bustout strategy is to appear as legitimate consumers in order to increase their credit limits over time. They typically make purchases and timely payments during the early life of their accounts, and avoid scrutiny by acting like model customers. As a result, even the most sophisticated lenders often struggle to understand the true size of their first-party fraud problem, as many of their losses are masked as collections charge-offs. That s why we created the Opera Solutions Bustout Application, a unique, advanced analytic approach that rides on our Credit & Risk Signal Hub to help lenders understand the actual size of their bustout fraud problem and implement new analytic tools to identify and prevent it earlier than ever before possible. And it s already realizing significant savings: we re delivering $4-$8MM a year for each $10B in receivables for issuers that already have a bureau-based bustout scoring system in place, and even more for those without any scoring system. The problem: bad actors who look like model citizens In many ways, bustout fraud is a crime of opportunity. Sometimes, consumers in dire financial straits desperately apply for credit while their profiles are still adequate to get the accounts approved. In other cases, something far more nefarious is at work: organized crime rings, based here and abroad, recruit consumers to perpetrate this fraud. Whatever the impetus, these consumers typically make modifications or embellishments to their application information, creating a fragmented file at the credit bureaus and allowing them to claim they have been victims of identity theft once their accounts go delinquent and collectors begin to call. Opera Solutions Credit & Risk Signal Hub technologies have the capability to identify the Signals these activities create, quickly and accurately differentiating between the commonplace and the criminal.

3 3 Find more bustout, earlier Savings achieved by detecting bustout earlier 50-55% 25-30% New cases identified using behavioral signatures 10-55% 100% New cases identified using link analysis The sophisticated algorithms of our Credit & Risk Signal Hub technologies pick up the faint Signals of high-risk behavioral signatures for each of the bustout patterns, and do so earlier enabling lenders to take swift action on more bustout activity, and thereby prevent many millions of dollars in losses. Currently Detected Currently Undetected Detected Through Linking Total There are three typical patterns to bustout cases: Rapid, Collusive Merchant, and Long Play. In each, fraudsters spend and pay normally for the first few months, seeking to appear as a typical consumer. Then the patterns change. Rapid Fraudsters rapidly increase spending through purchases, balance transfers, and/or convenience checks. A large payment is made, which frees up even more opportunity to buy. Collusive Merchant Large purchases are made at a single (often newer) merchant. Then payments cease. Long Play Spending and payments increase over many months. Credit limit increases are requested and granted. The customer makes several payments by check and continues to spend up to his or her full credit limit. Then, payments bounce. The solution: better and earlier identification through advanced analytics Each of these schemes has a unique behavioral signature, but each is hard to detect before the damage is done. Indeed, many lenders don t even realize they have been victimized; up to 50% of all bustout cases currently go completely undetected. Using advanced analytics, however, the Opera Solutions Bustout Application offers a far more comprehensive and effective solution to identify nefarious activity and stop bustout in its tracks.

4 4 We apply an advanced, highly-tuned ensemble model that brings together some of the world s most advanced pattern and anomaly detection algorithms against your daily flow of transaction activity, payment activity, and non-monetary transactions. Our approach allows us to pick up the earliest, subtlest signs of bustout, while defining dozens of metrics to serve as objective criteria for taking action and giving lenders the ability to accurately and quickly restrict future authorizations, or suspend suspect accounts. Opera Solutions Bustout Application finds the Signals that tell you what s really going on with your accounts. Purchase Patterns Payment Patterns Shut off Behavior Over Time Purchase Payment Credit line Increase Request Alert Bustout and credit abuse savings Earlier Detection (Days) Reducing the time to detection has major impact on loss avoidance for lenders. For example, Opera Solutions helped one client save over $60MM annually by identifying bustout cases seven days earlier Dollars (Millions) When it comes to bustouts and other frauds, make sure you re on the right side of Gotcha! For more information about the Opera Solutions Bustout Application, and to learn how our Credit & Risk Signal Hub technologies can help you combat other frauds, please contact us at CreditandRiskServices@operasolutions.com.

5 ABOUT OPERA SOLUTIONS, LLC: Opera Solutions drives productivity for enterprise and government through advanced Big Data predictive analytics that create machine-generated directed actions to significantly improve front-line decisions. Its Signal Hub technologies provide organizations an enterprise-wide capability to continually extract and put to use newly available predictive information from outside their firewalls, creating a revolutionary pathway to productivity, profit, and advantage. With 230+ data scientists among its 700 employees, the company is an internationally recognized leader in machine learning. It serves enterprises in Financial Services, Healthcare, Government, Supply Chain, Marketing, and other sectors, with offices in North America, Europe, India, and China. New York Jersey City Boston Washington, DC San Diego London Shanghai New Delhi

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