What are You Saying? Using Topic to Detect Financial Misreporting

101 Pages Posted: 5 Jul 2016 Last revised: 23 May 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

Date Written: May 14, 2019

Abstract

This study uses a machine learning technique to assess whether the thematic content of financial statement disclosures (labeled as 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 the 1994 to 2012 period. We find that the algorithm produces a valid set of semantically meaningful topics that are predictive of financial misreporting based on samples of SEC enforcement actions (AAERs) and reporting 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 as an additional predictor significantly outperform traditional models when detecting long-duration misreporting events. Taken together, our results suggest that the content of annual report narratives and the attention devoted to each topic are useful signals in detecting financial misreporting.

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

Suggested Citation

Brown, Nerissa C. and Crowley, Richard M. and Elliott, W. Brooke, What are You Saying? Using Topic to Detect Financial Misreporting (May 14, 2019). 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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