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Traditional modeling and tuning of rules-based systems – while effective at detecting known and recurring patterns of fraud – often return exceptionally high numbers of false positive alerts, mistakenly flag legitimate behaviors as suspicious, and more importantly, are exploited by fraudsters as they learn the rules and how to circumvent them. This white paper summarizes a candid discussion with fraud experts from SAS and Bank of America about what it takes to develop more customer-centric fraud management – factoring in anomaly detection, customer baseline scoring and customer-prescribed risk appetites – to help identify suspicious transactions and networks before the money leaves your premises.
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