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International Conference on Swarm, Evolutionary, and Memetic Computing

SEMCCO 2014: Swarm, Evolutionary, and Memetic Computing pp 239–250Cite as

Fraud Detection in Financial Statements Using Evolutionary Computation Based Rule Miners

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8947))

Abstract

In this paper, we propose new rule based classifiers based on Firefly (FF) and Threshold Accepting (TA) Algorithms viz., Improved Firefly Miner, Threshold Accepting Miner, Hybridized Firefly-Threshold Accepting (FFTA) based Miner for classifying a company as fraudulent or non fraudulent with respect to their financial statements. We apply t-statistic based feature selection and investigate its impact on the results. FFTA and TA miners turned to be statistically similar. Both algorithms outperformed standard decision tree both in terms of sensitivity and the length of rules.

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Author information

Authors and Affiliations

  1. Center of Excellence in CRM and Analytics, Institute for Development and Research in Banking Technology, Castle Hills Road #1 Masab Tank, Hyderabad, 500057, Andhra Pradesh, India

    Ganghishetti Pradeep, Vadlamani Ravi, B. L. Deekshatulu & A. Aditya

  2. SCIS, University of Hyderabad, Hyderabad, 500046, Andhra Pradesh, India

    Ganghishetti Pradeep

  3. Indian Institute of Technology, Patna, 800013, Bihar, India

    Kaushik Nandan

  4. IIM Calcutta, Kolkata, 700104, West Bengal, India

    Indranil Bose

Authors
  1. Ganghishetti Pradeep
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  2. Vadlamani Ravi
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  3. Kaushik Nandan
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  4. B. L. Deekshatulu
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  5. Indranil Bose
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  6. A. Aditya
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Corresponding author

Correspondence to Vadlamani Ravi .

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Editors and Affiliations

  1. Department of Electrical Engineering, IIT, New Delhi, India

    Bijaya Ketan Panigrahi

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Ponnuthurai Nagaratnam Suganthan

  3. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India

    Swagatam Das

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Pradeep, G., Ravi, V., Nandan, K., Deekshatulu, B.L., Bose, I., Aditya, A. (2015). Fraud Detection in Financial Statements Using Evolutionary Computation Based Rule Miners. In: Panigrahi, B., Suganthan, P., Das, S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2014. Lecture Notes in Computer Science(), vol 8947. Springer, Cham. https://doi.org/10.1007/978-3-319-20294-5_21

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  • DOI: https://doi.org/10.1007/978-3-319-20294-5_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20293-8

  • Online ISBN: 978-3-319-20294-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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