Assistant Professor Richard Crowley from SMU’s School of Accountancy examines financial accounting using both archival and analytical methods for his research.  Much of his archival work deals with large sets of unstructured data using high-powered computing algorithms to address accounting issues that are otherwise infeasible to approach.

He has recently written two research articles on using a machine learning technique to assess the content of companies’ disclosures.  In this podcast, he discusses how fraud and misreporting can be detected by studying a company’s financial statement using a machine learning technique, and shares how companies disclose financial information on Twitter, and how feedback from investors and others can influence this.