This talk focuses on data analytics, AI, and machine learning, examinig different uses cases for methods. Examples include portfolio allocation using statistics, misreporting detection using machine learning, and transformer neural network applications.

This talk extends on Brown, Crowley, and Elliott (2020, JAR) by discussing time-variation in misreporting predictability and demonstrating the effectiveness of nonparametric ML-based methods for prediction.

Summer camp lecture presented to the IIM Calcutta Summer Camp, 2021

Public lecture on “Using Machine Learning to Detect Financial Fraud.”

Slides from the SMU PhD Research Workshop + Information Session

Slides from my Data Science Singapore (DSSG) talk

A brief overview of using machine learning to detect financial misreporting at scale.

Detecting financial misreporting by leveraging the information firms wrote in their annual reports.