BankSealer: A decision support system for online banking fraud analysis and investigation
We develop a framework for semi-supervised outlier-detection based on models to discover online banking frauds. We provide a score with a clear statistical meaning, able to deal with concept drift, scarce and non-stationary data. We develop an in-depth analysis of a real-world online banking dataset, in which we highlight the main challenges. We perform test on real-world data, injecting a realistic set of attacks. The system ranks frauds up to 98% detection rate. Given the good results, a leading Italian bank deploys a prototype of the system in their environment to analyze frauds.
decision support system internet banking fraud detection user profiling