Machine Learning Tools for Finance and FinTech

In this chapter, we place the reader squarely into the DDF Model selection section and expose recent developments in ML and AI techniques as applied to finance and banking arena. We start with a simple ordinary least square (OLS) model and proceed to exposing, LASSO regression, decision tree model and random forest modeling framework, concluding with the exposition of recurrent neural network (RNN) architecture from conceptual, mathematical and programmatic standpoints. Recurrent neural networks (RNNs) are widely used in finance due to their ability to process sequential data and capture temporal dependencies. The sequential nature of financial data, in quantitative as well as qualitative formats, makes RNNs particularly valuable tool, as they can remember previous states and use that information to make predictions about future conditions.