The Role of Employee Reviews in Fraud Detection

1 Pages Posted: 20 Dec 2024

See all articles by Allen H. Huang

Allen H. Huang

Hong Kong University of Science and Technology - Department of Accounting

Juanting Wang

Shanghai University of Finance and Economics

Shiheng Wang

Hong Kong University of Science & Technology (HKUST)

Date Written: June 24, 2024

Abstract

This paper examines whether employees' public disclosure is useful for predicting accounting fraud. Using data from Glassdoor, we find that employees' ratings of senior management and the overall company, as well as their textual assessments of the quality of their employers' social and governance practices and the corporate culture, can predict accounting fraud. The fraud predictability of employee reviews we document is incremental to F-score and signals from capital market participants, and begins as early as two years before a fraud revelation. Additional analyses show that employee reviews are more useful for predicting fraud when they aggregate opinions from a more diverse and better educated labor force, and when employees have access to higher-quality internal information and enjoy stronger protection from employers. In sum, our evidence suggests that employee reviews are an important source of fraud-related information for the public and thus have practical implications for investors and regulators. Data Availability: Data are available from the public sources cited in the study.

Keywords: fraud prediction, employee review, Glassdoor, F-score

Suggested Citation

Huang, Allen H. and Wang, Juanting and Wang, Shiheng, The Role of Employee Reviews in Fraud Detection (June 24, 2024). Available at SSRN: https://ssrn.com/abstract=4996601 or http://dx.doi.org/10.2139/ssrn.4996601

Allen H. Huang

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

Juanting Wang (Contact Author)

Shanghai University of Finance and Economics ( email )

777 Guoding Road
Shanghai, AK Shanghai 200433
China

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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