The Usefulness of Credit Ratings for Accounting Fraud Prediction

51 Pages Posted: 21 Aug 2019 Last revised: 6 Sep 2023

See all articles by Allen H. Huang

Allen H. Huang

Hong Kong University of Science and Technology - Department of Accounting

Pepa Kraft

HEC Paris

Shiheng Wang

Hong Kong University of Science & Technology (HKUST)

Date Written: August 14, 2019

Abstract

This study examines whether and when credit ratings are useful for accounting fraud prediction. We find that negative rating actions by Standard & Poor’s (S&P), an issuer-paid credit rating agency (CRA), have predictive ability for fraud incremental to fraud prediction models (e.g., F-score) and other market participants. In contrast, rating actions by Egan-Jones Rating Company (EJR), an investor-paid CRA relying on public information, have less predictive ability, which is subsumed by S&P and other market participants. Our results are robust to including firms not covered by EJR, using only rating downgrades, controlling for firm characteristics, and using alternative benchmarks. We also find that the ability of negative S&P rating actions to predict fraud becomes stronger after the 2008–2009 financial crisis. Last, compared to EJR, S&P is quicker to take negative rating actions against fraud firms. In sum, our results suggest that issuer-paid CRAs’ information advantage helps predict accounting fraud.

Keywords: accounting fraud; fraud prediction; credit rating agency; issuer-paid rating agency; investor-paid rating agency; F-score

JEL Classification: G24, K22, M41

Suggested Citation

Huang, Allen H. and Kraft, Pepa and Wang, Shiheng, The Usefulness of Credit Ratings for Accounting Fraud Prediction (August 14, 2019). The Accounting Review, Forthcoming, HEC Paris Research Paper No. ACC-2019-1348, HKUST Business School Research Paper No. 2023-118, Available at SSRN: https://ssrn.com/abstract=3438846 or http://dx.doi.org/10.2139/ssrn.3438846

Allen H. Huang (Contact Author)

Hong Kong University of Science and Technology - Department of Accounting ( email )

LSK Business School Building
HKUST
Clear Water Bay, Kowloon
Hong Kong

HOME PAGE: http://www.AllenHuang.org

Pepa Kraft

HEC Paris ( email )

Jouy-en-Josas
France
644161543 (Phone)

HOME PAGE: http://www.hec.edu/Faculty-Research/Faculty-Directory/KRAFT-Pepa2

Shiheng Wang

Hong Kong University of Science & Technology (HKUST) ( email )

Clear Water Bay
Kowloon, 999999
Hong Kong
(852) 2358 7570 (Phone)
(852) 2358 1693 (Fax)

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