Using Quantitative Methods to Detect Financial Statement Manipulation for SMEs in an emerging market: Case of Albania

This paper examines the effectiveness of the Beneish M-Score model in identifying financial statement manipulation among small and medium entities in an emerging and under-researched market such as Albania. Using a sample of 247 Albanian companies across various sectors, the study applies the M-Score financial statements from years 2022 and 2023 to assess the model’s relevance in the Albanian economic context. Findings indicate varying degrees of alignment with the M-Score’s fraud detection benchmarks, reflecting both successful identification of potential manipulation and limitations due to regional economic characteristics and timeliness restrictions of the model application. Additionally, the study integrates Pearson correlation analysis to evaluate the relationship between Beneish variables and manipulation risks, identifying as key predictors the Days Sales in Receivables Index (DSRI), Sales Growth Index (SGI), and Leverage Index (LVGI). This dual approach enhances the understanding of the M-Score’s practical application and highlights its potential for detecting financial statement manipulation in emerging markets. By providing a robust framework for financial transparency, this research underscores the importance of tools like the M-Score in fostering trust within Albania’s corporate and financial sectors. JEL: M41, M42, M21