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Beyond the Neural Network: Analyzing, Investigating and Integrating Key to Fraud Management

In recent years, growing losses from fraud have cost financial institutions millions upon millions of dollars. According to Visa International, gross fraud from debit and credit cards is up 29% in 2005 over 2004. TowerGroup predicts that fraud from debit cards alone will surpass $1 billion USD in 2006. Fraudsters...

By Staff Writer | Updated on May 08, 2007

In recent years, growing losses from fraud have cost financial institutions millions upon millions of dollars. According to Visa International, gross fraud from debit and credit cards is up 29% in 2005 over 2004. TowerGroup predicts that fraud from debit cards alone will surpass $1 billion USD in 2006. Fraudsters have become more sophisticated, more organized and more international in scope than ever before. Financial institutions are under attack on a daily basis and continue to experience losses even with various fraud control mechanisms in place.

In response to this growth in transaction-based card fraud, most issuers have made use of neural networks and behavioral models to distinguish normal cardholder activity from fraudulent. While neural network technology and scoring models provide the base for nearly all fraud service programs, there are additional areas upon which issuers can focus to further improve their profitability by reducing fraud losses.

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