F4-B DeepFin: Federated Learning for Risk Management with Transparency and Accountability

PIs: Andy Li, Amy Pan

The goal of this project is to develop a Deep Neural Network based risk management model that can help financial companies predict loan default likelihood with a higher accuracy when a customer applies for a loan. The DNN model will be developed based on a new learning pattern called Federated Learning [1]. Since financial companies may be required to explain to their customers or government a decision made by one of its algorithms in a simple and logical way, we will further develop some ways of how to explain and analysis the performance of our model by important feature visualization and statistic model.


  1. Konečný J, McMahan HB, Yu FX, Richtárik P, Suresh AT, Bacon D. Federated learning: Strategies for improving communication efficiency. arXiv preprint arXiv:1610.05492. 2016 Oct 18.