Selecting Indicators of Predicting Fraud Risk. Case Study for Romanian Business Environment

EasyChair Preprint no. 9304

Abstract

The act of fraud has been practiced since ancient times and manifests itself in different ways. The aim of the study is to apply the Beneish score on Romanian firms and to identify which indicators are sensitive to the state of fraud. The sample was selected from the Bucharest Stock Exchange and consists of 66 companies traded on the main market for the years 2016-2021. The collected data were analyzed by year-by-year and cross-sectional methods (panel data) using manually collected information extracted from financial statements downloaded from the Bucharest Stock Exchange. Based on this data, the Beneish score was calculated and then statistical tests were performed. Using the results obtained from the Beneish Score calculation, we were able to divide the companies into two groups. The results clearly show that the group with no likelihood of fraud risk has lower scores for the eight indicators and the bankruptcy group has lower values. We identified sensitive items in both states such as DSRI (Days Sales Receivable Index), GMI (Gross Margin Index), SGAI (Selling General and Administrative Expense Index). In conclusion, several theories or hypotheses are offered to explain the underlying motivations for fraud. Romanian companies listed on regulated markets can be classified into risk groups in terms of fraudulent financial statements by applying the Beneish score. After statistical processing, it was concluded that not all models existing in the literature can be applied to any sample and cannot have the same purpose, because the type of companies differs, the financial data changes from one year to another, the object of activity changes from one year to another.

Keyphrases: Beneish, fraud, Fraud triangle theory, Romanian company

@Booklet{EasyChair:9304,
  author = {Ioana Lavinia Safta Pleșa and Andrada Ioana Sabău Popa and Nicolae Sorin Borlea and Anastasia Ciubotaru},
  title = {Selecting Indicators of Predicting Fraud Risk. Case Study for Romanian Business Environment},
  howpublished = {EasyChair Preprint no. 9304},

  year = {EasyChair, 2022}}