Profile of the fraudulent customer

Anna Matuszyk; Aneta Ptak-Chmielewska

Published : 2023-11-21

Vol. 59 No. 2 (2015)

Profile of the fraudulent customer

Anna Matuszyk

Aneta Ptak-Chmielewska

Abstract

When there is an economic downturn, financial crime proliferates and people are more likely to commit fraud. One of the most common frauds is when a loan is secured without any intention of repaying it. Credit crime is a significant risk to financial institutions and has recently led to increased interest in fraud prevention systems. The most important features of such systems are the determinants (warning signals) that allow you to identify potentially fraudulent transactions. The purpose of this paper is to identify warning signals using the following data mining techniques - logistic regression, decision trees and neural networks.
Proper identification of the determinants of a fraudulent transaction can be useful in further analysis, i.e. in the segmentation process or assignment of fraud likelihood. Data obtained in this way allows profiles to be defined for fraudulent and non-fraudulent applicants. Various fraud-scoring models have been created and presented.

Keywords:

personal loan fraud, fraud determinants, profile of the fraudulent customer

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Matuszyk, A., & Ptak-Chmielewska, A. (2023). Profile of the fraudulent customer. Safe Bank, 59(2), 7–24. Retrieved from https://ojs.bfg.pl/index.php/bb/article/view/337

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Anna Matuszyk

anna.matuszyk@sgh.waw.pl

Affiliation:
Warsaw School of Economics Poland

Aneta Ptak-Chmielewska

aptak@sgh.waw.pl

Affiliation:
Warsaw School of Economics Poland