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Decision Tree Approach to Discovering Fraud in Leasing Agreements

Decision Tree Approach to Discovering Fraud in Leasing Agreements Abstract 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. Objectives: The goal of the paper is to estimate the usability of the data mining approach in discovering fraud in leasing agreements. Methods/Approach: Real-world data from one Croatian leasing firm was used for creating tow models for fraud detection in leasing. The decision tree method was used for creating a classification model, and the CHAID algorithm was deployed. Results: The decision tree model has indicated that the object of the leasing agreement had the strongest impact on the probability of fraud. Conclusions: In order to enhance the probability of the developed model, it would be necessary to develop software that would enable automated, quick and transparent retrieval of data from the system, processing according to the rules and displaying the results in multiple categories. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Business Systems Research Journal de Gruyter

Decision Tree Approach to Discovering Fraud in Leasing Agreements

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Publisher
de Gruyter
Copyright
Copyright © 2014 by the
ISSN
1847-9375
eISSN
1847-9375
DOI
10.2478/bsrj-2014-0010
Publisher site
See Article on Publisher Site

Abstract

Abstract 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. Objectives: The goal of the paper is to estimate the usability of the data mining approach in discovering fraud in leasing agreements. Methods/Approach: Real-world data from one Croatian leasing firm was used for creating tow models for fraud detection in leasing. The decision tree method was used for creating a classification model, and the CHAID algorithm was deployed. Results: The decision tree model has indicated that the object of the leasing agreement had the strongest impact on the probability of fraud. Conclusions: In order to enhance the probability of the developed model, it would be necessary to develop software that would enable automated, quick and transparent retrieval of data from the system, processing according to the rules and displaying the results in multiple categories.

Journal

Business Systems Research Journalde Gruyter

Published: Sep 10, 2014

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