Decision Tree Approach to Discovering Fraud in Leasing Agreements

Other literature type, Article English OPEN
Horvat Ivan; Pejić Bach Mirjana; Merkač Skok Marjana;
  • Publisher: Sciendo
  • Journal: Business Systems Research,volume 5,issue 2 (issn: 1847-9375, eissn: 1847-9375)
  • Related identifiers: doi: 10.2478/bsrj-2014-0010
  • Subject: cars | decision tree | HF5001-6182 | Business | data mining | G32 | fraud detection | decision tree; fraud detection; leasing fraud; cars; data mining; leasing agreements | leasing agreements | O31 | leasing fraud

Background: Fraud attempts create large losses for financing subjects in modern economies. At the same time, leasing agreements have become more and more popular as a means of financing objects such as machinery and vehicles, but are more vulnerable to fraud attempts. O... View more
  • References (12)
    12 references, page 1 of 2

    1. Apté, C., Weiss, S. (1997), “Data mining with decision trees and decision rules”, Future Generation Computer Systems, Vol. 13, No. 2-3, pp. 197-210.

    2. Bhattacharyya, S., et al. (2011), “Data mining for credit card fraud: A comparative study”, Decision Support Systems, Vol. 50, No. 3, pp. 602-613.

    3. Coussement, K., Van den Bossche, F. A., De Bock, K. W. (2014), “Data accuracy's impact on segmentation performance: Benchmarking RFM analysis, logistic regression, and decision trees”, Journal of Business Research, Vol. 67, No. 1, pp. 2751-2758.

    4. Huang, S. Y., Tsaih, R. H., Lin, W. Y. (2012), “Unsupervised neural networks approach for understanding fraudulent financial reporting”, Industrial Management & Data Systems, Vol. 112, No. 2, pp. 224-244.

    5. Li, X. B. (2005), “A scalable decision tree system and its application in pattern recognition and intrusion detection”, Decision Support Systems, Vol. 41, No. 1, pp.112-130.

    6. McCarty, J. A., Hastak, M. (2007), “Segmentation approaches in data-mining: A comparison of RFM, CHAID, and logistic regression”, Journal of Business Research, Vol. 60, No. 6, pp. 656-662.

    7. Morais, A. I. (2013), “Why companies choose to lease instead of buy? Insights from academic literature”, Academia Revista Latinoamericana de Administración, Vol. 26, No. 3, pp. 432-446.

    8. Ngai, E.W.T. et al. (2011), “The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature”, Decision Support Systems, Vol. 50, No. 3, pp. 559-569.

    9. Sinha, A.T., Zhao, H. (2008), “Incorporating domain knowledge into data mining classifiers: An application in indirect lending”, Decision Support Systems, Vol. 46, No. 1, pp. 287-299.

    10. Smith, C. W., Wakeman, L. M. (1985), “Determinants of corporate leasing activity”, Journal of Finance, Vol. 40, No. 3, pp. 895-911.

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