Custom AI Solutions: AI Machine Learning Fraud Detection

To meet the bank’s goals, our solution needed to identify fraudulent checks in real time, as well as reduce the number of checks requiring manual review. The bank already uses optical character recognition (OCR) and deep learning technology to scan checks, process data and verify signatures. Our model, based on Google TensorFlow™, uses a neural network to parse a historical database of previously scanned checks, including those known to be fraudulent.

We trained the neural network to use a set of comparative algorithms to distinguish good checks from anomalous ones. By automatically comparing various factors on scans of deposited checks to those in the database, our model flags potential counterfeits in real time. It assigns a confidence score to each scanned check, flagging it as good, fraudulent or needing further review. Our solution is scalable and configurable to the client’s evolving needs.

Counterfeiters constantly develop new techniques to perpetrate fraud in financial services. Our AI solution operates with near-human intelligence to counteract the counterfeiters and reduce losses. Every transaction the model processes increases its accuracy of detection and adds to its enormous repository of historical information, so it’s continually learning the practices of habitual fraudsters to defeat them.