Bank Fraud Detection

We work with you to address your most critical business priorities.

There are many variations of passages of Lorem Ipsum available, but the majority have suffered alteration in some form, by injected humour, or randomised words which don’t look even slightly believable.

  • Client : Bank
  • Category : Ai & ML
  • Date : 08/01/2020

Mitigating fraud is a top priority for banks. fraudsters are becoming more creative and technologically savvy—they’re also using advanced technologies like machine learning—and new schemes to defraud banks are evolving rapidly.

Analytic approach employs a “champion/ challenger” methodology. With this approach, deep learning systems compare models in real time to determine which one is most effective. Each challenger processes data in real time, learning as it goes which traits are more likely to indicate fraud. If a process dips below a certain threshold, the model is fed more data, such as the geo-location of customers or recent ATM transactions. 

When a challenger outperforms other challengers, it transforms into a champion, giving the other models a roadmap to successful fraud detection