Artificial Intelligence and Machine Learning in Corporate Finance

Abstract

This chapter examines how artificial intelligence and machine learning are utilized in corporate finance research. It provides an overview of the applications and identifies three main goals for using machine learning in data analysis: (1) predicting independent variables or identifying variables that support predictions, (2) uncovering patterns in data, and (3) enhancing causal inferences. The chapter discusses how machine learning techniques are tailored to exploit large datasets, offering advantages when dealing with numerous variables, nonlinear relationships, and the need for out-of-sample predictive accuracy. The chapter also provides examples of machine learning applications for processing and utilizing unstructured data, allowing researchers to quantify constructs that have previously been difficult to capture in corporate finance research. Although applications in classic corporate finance fields remain scarce, the chapter outlines two promising examples: mergers and acquisitions and default prediction.