Fraud and Anomaly Detection

The BSA Tracker’s Anomaly Detection and Fraud reports are highly targeted and based on evidence-based indicators to identify and track potential fraud. This next generation approach is designed to help address the challenges of traditional risk detection software engines.

The following “real” case studies or examples of fraud cases, based on the Anomaly Detection alerts and the Branch Workshop in the BSA Tracker.

Evidence-based detection is objective; it uses precise, unambiguous measures to assess irregularities or anomalies in account transactions and patterns. This approach assures that evidence is replicable by maintaining transparency of the methods used to collect the information.

The BSA Tracker solution combines enhanced transaction source information, with geo-location and transactional modeling with critical fraud indicators. This information is correlated using big data technologies to analyze events across time, users and activities. This type of anomaly detection is different than internet fraud detection services provided by some core systems.

Using this information, the Tracker completely integrates the “know your customer/member” (KYC) and enhanced due diligence (EDD) data into the decision process for identifying irregular transactions based on amounts, the location of the source transaction location of the customer/member and his work, etc.

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