U.S. flag

An official website of the United States government, Department of Justice.

Dot gov

The .gov means it’s official.
Federal government websites always use a .gov or .mil domain. Before sharing sensitive information online, make sure you’re on a .gov or .mil site by inspecting your browser’s address (or “location”) bar.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Enhancing Corporate Crime Enforcement with Machine Learning--A Multidisciplinary Risk Factor Approach

Award Information

Award #
2019-R2-CX-0008
Location
Awardee County
Ingham
Congressional District
Status
Awarded, but not yet accepted
Funding First Awarded
2019
Total funding (to date)
$28,282

Description of original award (Fiscal Year 2019, $28,282)

The proposed dissertation research will use machine learning to develop a risk-assessment algorithm to aid in corporate financial statements and reporting fraud (FSRF) detection. The project will use SEC Audit and Enforcement Releases (AAERs) data from 2002-2018 and corresponding SEC prosecution data. Fraudulent firms will be matched with non-fraudulent firms using SEC annual reports (10-Ks) to assist in identification of risk factors. The applicant proposes to use random forest (to model the complex decision-making process underlying fraudulent reports) and deep network (to model unobservable processes) machine learning techniques to train and test the risk assessment algorithm. These methods are superior to other commonly used statistical methods that have difficulty with non-linear relationships, smaller degrees of freedom, and multi-collinearity. Finally, the algorithm will be made available to criminal and regulatory agencies through targeted research briefs and publication in trade journals. "Note: This project contains a research and/or development component, as defined in applicable law," and complies with Part 200 Uniform Requirements - 2 CFR 200.210(a)(14). CA/NCF
Date Created: September 13, 2019