Izvorni znanstveni članak
https://doi.org/10.2478/bsrj-2014-0010
Decision Tree Approach to Discovering Fraud in Leasing Agreements
Ivan Horvat
orcid.org/0000-0003-0084-0547
; VB Leasing d.o.o., Croatia
Mirjana Pejić Bach
orcid.org/0000-0003-3899-6707
; Faculty of Economics & Business – Zagreb, University of Zagreb, Croatia
Marjana Merkač Skok
; Fakulteta za poslovne in komercijalne vede, Slovenia
Sažetak
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.
Ključne riječi
decision tree; fraud detection; leasing fraud; cars; data mining; leasing agreements
Hrčak ID:
125679
URI
Datum izdavanja:
16.6.2014.
Posjeta: 1.446 *