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Predicting Financial Statement Frauds Using Machine Learning Methods and Logistic Regression: The Case of Borsa Istanbul

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  • Barış Aksoy

    (Sivas Cumhuriyet University)

Abstract

This study aims to create an effective model to predict one year before whether 88 firms, continuously traded at Borsa Istanbul between 2000- 2019, commit fraud in their financial statements. For this purpose, financial statement fraud was predicted by using Artificial Neural Networks (ANN), Classification and Regression Trees (CART) and Support Vector Machine (SVM) and Logistic Regression (LR) methods among machine learning methods. As a result, the overall prediction accuracy of ANN (96.15%), CART (96.15%), SVM (80.77%) and LR (80.77%) test samples were obtained. ANN and CART classified correctly in test samples all 13 firms that fraudulent in their financial statements. This shows that all methods used in this study, can be used in studies to predict financial statement fraud.

Suggested Citation

  • Barış Aksoy, 2021. "Predicting Financial Statement Frauds Using Machine Learning Methods and Logistic Regression: The Case of Borsa Istanbul," Journal of Finance Letters (Maliye ve Finans Yazıları), Maliye ve Finans Yazıları Yayıncılık Ltd. Şti., vol. 36(115), pages 27-58, April.
    • Handle: RePEc:acc:malfin:v:36:y:2021:i:115:p:27-58
    DOI: https://doi.org/10.33203/mfy.733855
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    More about this item

    Keywords

    Financial Statement Fraud; Machine Learning Methods; Logistic Regression; Borsa Istanbul;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • M42 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Auditing

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