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Volume 9 Issue 3 - January 2018

  • 1. Fraudulent financial statements: detection modeling using data mining

    Authors : Hiral Patel, Dr. Satyen Parikh

    Pages : 8-14

    DOI : http://dx.doi.org/10.21172/1.93.02

    Keywords : fraudulent Company, BSE, Data Mining, Financial Ratio, Predictive Model

    Abstract :

    A rising incidents of financial frauds in recent time has increased the risk of investor and other stakeholders. Hiding of financial losses through fraud or manipulation in reporting and hence resulted into erosion of considerable wealth of their stakeholders. In fact, a number of global companies like WorldCom, Xerox, Enron and number Indian companies such as Satyam, Kingfisher and Deccan Chronicle had committed fraud in financial statement by manipulation. Hence, it is imperative to create an efficient and effective framework for detection of financial fraud. This can be helpful to regulators, investors, governments and auditors as preventive steps in avoiding any possible financial fraud cases. In this context, increasing number of researchers these days have started focusing on developing systems, models and practices to detect fraud in early stage to avoid the any attrition of investor’s wealth and to reduces the risk of financing. In Current study, the researcher has attempted to explore the various Data Mining (DM) techniques to detect fraud in financial statements (FFS). To perform the experiment, researcher has chosen 86 FFS and 92 non-fraudulent financial statements (non-FFS) of manufacturing firms. The data were taken from Bombay Stock Exchange for the dimension of 2008-2011. Auditor’s report is considered for classification of FFS and Non-FFS companies. T-test was applied on 31 important financial ratios and 10 significant variables were taken in to consideration for data mining techniques. 86 FFS and 92 non-FFS during 2008-2017 were taken for testing data set. Researcher has trained the model using data sets. Then, the trained model was applied to the testing data set for the accuracy check.

    Citing this Journal Article :

    Hiral Patel, Dr. Satyen Parikh, "Fraudulent financial statements: detection modeling using data mining", Volume 9 Issue 3 - January 2018, 8-14

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