Nov 03, 2010
Banks can significantly reduce their bad debt levels and collections expenses, by identifying first-party fraud cases before they reach collections. Advanced network analytics is the key to early detection and prevention of threats before they result in large losses.
First-party fraud occurs when customers apply for credit cards, loans, overdrafts or other un-secured banking credit lines with no intention of paying. Often these customers will collaborate with bank employees to assist them in their fraudulent activities. Once a bank�s customer, these fraudsters need to build up their credit score to increase their achievable credit lines and maximize their eventual earnings.
First-party fraudsters often �fly below the radar� of analytics which are commonly used by banks today. This is because traditional analytics are not well equipped to find first-party fraud and also because fraudsters are adept at using various techniques to determine the rules and thresholds, often assisted by bank employees, thus avoiding the triggering of alarms. Conventional fraud analytics only look at the individual account holder behavior which typically does not trigger any alarms as fraudsters are highly skilled at generating �normal� behavior within those accounts.
The Detica NetReveal� platform uses social network analysis to uncover fraudulent networks and, typically, at a much earlier point in the cycle. It flags further applications from succeeding and allows investigators to review the current levels of available credit to those accounts linked to the fraudulent network.