Detecting financial statement fraud in listed companies using financial econometric models: the case of Luckin Coffee Inc.

Abstract

This paper examines how financial econometric models can be used to identify financial statement fraud in listed companies, using Luckin Coffee Inc. as a case study. Luckin Coffee was selected because it is a well-known publicly listed company whose accounting scandal has been documented by regulatory authorities, while its rapid-growth business model provides a suitable setting for quantitative fraud-risk analysis. The study combines a qualitative analysis of the mechanisms underlying the fraud with a concise empirical assessment based on the Beneish M-score and accrual-based indicators. The results reveal several measurable warning signs in the company's reporting environment in 2019, including abnormal sales growth, a widening gap between reported revenue and operating cash flow, inflated costs and expenses used to support fictitious sales, and increased leverage pressure following aggressive external financing. Even when the unstable accounts receivable ratio is treated conservatively, the resulting M-score remains above commonly used thresholds for manipulation risk. The study argues that financial econometric models cannot replace audit evidence, but they can serve as an effective early-warning tool for investors, auditors, and regulators. The primary contribution of this study is to demonstrate how model-based screening can be integrated with governance analysis into a practical framework for detecting fraud in listed companies.