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Financial Fraud Detection Model Based on Random Forest

Author

Listed:
  • Liu, Chengwei
  • Chan, Yixiang
  • Alam Kazmi, Syed Hasnain
  • Fu, Hao

Abstract

Business's accelerated globalization has weakened regulatory capacity of the law and scholars have been paid attention to fraud detection in recent years. In this study, we introduced Random Forest (RF) for financial fraud technique detection and detailed features selection, variables’ importance measurement, partial correlation analysis and Multidimensional analysis. The results show that a combination of eight variables has the highest accuracy. The ratio of debt to equity (DEQUTY) is the most important variable in the model. Moreover, we applied four statistic methodologies, including parametric and non-parametric models to construct detection models and concluded that Random Forest has the highest accuracy and the non-parametric models have higher accuracy than non-parametric models. However, Random Forest can improve the detection efficiency significantly and have an important practical implication.

Suggested Citation

  • Liu, Chengwei & Chan, Yixiang & Alam Kazmi, Syed Hasnain & Fu, Hao, 2015. "Financial Fraud Detection Model Based on Random Forest," MPRA Paper 65404, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:65404
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    File URL: https://mpra.ub.uni-muenchen.de/65404/1/MPRA_paper_65404.pdf
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    References listed on IDEAS

    as
    1. Alam Kazmi, Syed Hasnain, 2015. "Brand the Pricing: Critical Critique," MPRA Paper 64984, University Library of Munich, Germany.
    2. J. V. Hansen & J. B. McDonald & W. F. Messier, Jr. & T. B. Bell, 1996. "A Generalized Qualitative-Response Model and the Analysis of Management Fraud," Management Science, INFORMS, vol. 42(7), pages 1022-1032, July.
    3. Alam Kazmi, Syed Hasnain, 2015. "Developments in Promotion Strategies Review on Psychological Streams of Consumers," MPRA Paper 65424, University Library of Munich, Germany, revised 05 May 2015.
    4. Chen, Gongmeng & Firth, Michael & Gao, Daniel N. & Rui, Oliver M., 2006. "Ownership structure, corporate governance, and fraud: Evidence from China," Journal of Corporate Finance, Elsevier, vol. 12(3), pages 424-448, June.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Financial Fraud Detection; Random Forest; Ratio of debt to equity; Partial Correlation Analysis; Statistic methodologies; Parametric models;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • G00 - Financial Economics - - General - - - General
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics

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