Traditional profiling of observed patterns in suspicious transactions experiences limited success in actual detection due to the sheer volume of data that renders detailed analysis of individual transactions impossible. Booz Allen Hamilton has developed advanced modeling capabilities that can interpret large volumes of data and do the analysis necessary to develop strategies for predicted behavior.
Booz Allen can help financial institutions improve their Anti-Money Laundering/Counter-terrorist Financing (AML/CTF) programs and protect against illicit or fraudulent activities. Using a group of techniques—including agent-based modeling and neural networks—Booz Allen can assist banks in building anomaly detection models that identify suspicious activity and prevent fraud, waste, and abuse.
Application of Booz Allen’s proven predictive analytics methodology involves:
Predictive Analysis is a tool that financial institutions should include in their AML/CTF regimen. Compliance requirements concerning “Know your Customer” can be met by applying predictive analysis to customer behaviors. This effective technique can isolate anomalous types of behavior patterns that may have been adopted to evade regulations—such misleading wire transfer activity (smurfing) designed to circumvent interdiction software. Booz Allen can also apply predictive analysis to vulnerability testing of bank AML/CTF safeguards.
Booz Allen’s Advanced Analytics service offering combines the industry knowledge and analysis expe¬rience of our staff with the technical capabilities of predictive analytics and investigative software tools, allowing clients to perform comprehensive data analysis activities in just a few weeks. Booz Allen works closely with each client to develop the right solution, translating expertise into even more powerful, tailored analytic tools and techniques that produce definitive results for the client.
Manager focused on cyber technologies and their application among the firm’s clients.
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