Catch Me If You Can: Improving the Scope and Accuracy of Fraud Prediction

51 Pages Posted: 9 Apr 2019 Last revised: 15 Feb 2020

See all articles by Bidisha Chakrabarty

Bidisha Chakrabarty

Saint Louis University - Richard A. Chaifetz School of Business

Pamela C. Moulton

Cornell University - SC Johnson College of Business

Leonid Pugachev

Rochester Institute of Technology, Saunders College of Business

Xu (Frank) Wang

Saint Louis University - Chaifetz School of Business

Date Written: February 10, 2020

Abstract

We propose a parsimonious metric – the Adjusted Benford score (AB-score) – to improve the detection of financial misstatements. Based on Benford’s Law, which predicts the leading-digit distribution of naturally occurring numbers, the AB-score estimates a firm-year’s likelihood of financial statement manipulation, compared to its peers and controlling for time-series trends. The AB-score’s biggest advantage is coverage: It can be computed for about 60% more firm-years than the leading accounting-based metric (the F-score) without sacrificing accuracy. Notably, it can be computed for financial firms, which are often excluded from financial misconduct research due to data availability issues. For firm-years with all data available, combining the AB-score and F-score variables into one model yields higher accuracy in predicting misstatements. Our metric performs well out-of-sample as well as in-sample, across different misstatement databases, and for a set of notorious financial frauds. It should be especially useful to regulators and industry professionals.

Keywords: fraud; accounting quality; Benford’s Law; F-score; earnings manipulation; earnings misstatement

JEL Classification: G20, G23, M41

Suggested Citation

Chakrabarty, Bidisha and Moulton, Pamela C. and Pugachev, Leonid and Wang, Xu (Frank), Catch Me If You Can: Improving the Scope and Accuracy of Fraud Prediction (February 10, 2020). Available at SSRN: https://ssrn.com/abstract=3352667 or http://dx.doi.org/10.2139/ssrn.3352667

Bidisha Chakrabarty

Saint Louis University - Richard A. Chaifetz School of Business ( email )

3674 Lindell Blvd
St. Louis, MO MO 63108-3397
United States
3149773607 (Phone)
3149771479 (Fax)

HOME PAGE: http://business.slu.edu/departments/finance/faculty-staff/bidisha-chakrabarty

Pamela C. Moulton (Contact Author)

Cornell University - SC Johnson College of Business ( email )

Ithaca, NY 14853
United States

Leonid Pugachev

Rochester Institute of Technology, Saunders College of Business ( email )

OK
United States

Xu (Frank) Wang

Saint Louis University - Chaifetz School of Business ( email )

3674 Lindell Blvd
St. Louis, MO 63108-3397
United States

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