What are You Saying? Using Topic to Detect Financial Misreporting

67 Pages Posted: 5 Jul 2016 Last revised: 3 Dec 2019

See all articles by Nerissa C. Brown

Nerissa C. Brown

University of Illinois at Urbana-Champaign

Richard M. Crowley

Singapore Management University

W. Brooke Elliott

University of Illinois at Urbana-Champaign

Multiple version iconThere are 2 versions of this paper

Date Written: November 26, 2019

Abstract

We use a machine learning technique to assess whether the thematic content of financial statement disclosures (labeled topic) is incrementally informative in predicting intentional misreporting. Using a Bayesian topic modeling algorithm, we determine and empirically quantify the topic content of a large collection of 10-K narratives spanning 1994 to 2012. We find that the algorithm produces a valid set of semantically meaningful topics that predict financial misreporting, based on samples of SEC enforcement actions (AAERs) and irregularities identified from financial restatements and 10-K filing amendments. Our out-of-sample tests indicate that topic significantly improves the detection of financial misreporting by as much as 59% when added to models based on commonly used financial and textual style variables. Furthermore, models that incorporate topic significantly outperform traditional models when detecting serious revenue recognition and core expense errors. Taken together, our results suggest that the topics discussed in annual report filings and the attention devoted to each topic are useful signals in detecting financial misreporting.

Keywords: Topic, Disclosure, Latent Dirichlet Allocation, Financial Misreporting

JEL Classification: C80, K22, K42, M40, M41, M48

Suggested Citation

Brown, Nerissa C. and Crowley, Richard M. and Elliott, W. Brooke, What are You Saying? Using Topic to Detect Financial Misreporting (November 26, 2019). Journal of Accounting Research, Forthcoming, 27th Annual Conference on Financial Economics and Accounting Paper, Available at SSRN: https://ssrn.com/abstract=2803733 or http://dx.doi.org/10.2139/ssrn.2803733

Nerissa C. Brown (Contact Author)

University of Illinois at Urbana-Champaign ( email )

1206 South Sixth Street
Champaign, IL 61820
United States

Richard M. Crowley

Singapore Management University ( email )

60 Stamford Road
Singapore 178900
Singapore

HOME PAGE: http://rmc.link

W. Brooke Elliott

University of Illinois at Urbana-Champaign ( email )

1206 South Sixth Street
Champaign, IL 61820
United States

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