The use of AI in the financial services is not new; early predictive modeling tools, leveraging basic AI techniques like logistic regression and decision trees, were made commercially available through the late 70’s and early 80’s. Financial services have since grown to use an array of these and more complicated algorithms in areas such as targeted marketing, collections, and algorithmic trading. AI has long been embedded in many day-to-day business decisions and interactions, from targeted marketing to fraud alert.

And yet, recent advancements in the field are creating opportunities today that large Financial Services companies are struggling to capture, despite their many years in using AI. What are these opportunities and the associated challenges? We will go through the evolution of machine learning in earlier and recent years, and the many applications of AI in financial services, old and new, based on a series of practical examples and techniques.