New-Age Machine Learning Algorithms in Retail Lending

More than a decade back while joining a large US Credit Cards company, it was surprising to see that Predictive Analytics was limited to multivariate regression and logistic models. This was in contrast to previous stints at Start-Ups funded by NASA / NIST where a broader set of Machine Learning (ML) methods including SVMs, NNs, Random or Gradient Boosting Trees were regularly applied. There were a number of good reasons for using the simpler models in Retail Lending. Firstly, Decision Frameworks were already in place that made input feature selection a relatively simpler exercise. For e.g., for Credit Decisioning, one could think in terms of 5Cs of Credit (Character, Capacity, Capital, Collateral, Conditions), and search for Data variables that catered to them.