Analysis of Internal Fraud in the Microloan Process with Confirmatory Factor Analysis (CFA) and the Extreme Gradient Boosting (XGBoost) Method

DOI

10.2991/978-94-6463-144-9_23How to use a DOI?

Keywords

CFA; Fraud; Mitigation; Prevention; Prediction; XGBoost

Abstract

Internal fraud in the microcredit business process has caused significant losses to the banking industry and financial institutions. Internal fraud is one type of operational risk frequently faced by banks/financial institutions focusing on microcredit services. The typical fraud frequently found is Corruption and Misappropriation of Assets (ACFE). For instance, ‘Tempilan’ credit, Mask credit, and Fictitious Credit. Machine learning automatically predicts the possibility of internal fraud in the microloan business process. This research aimed to determine which the most dominant component from the theory of social identity and the fraud triangle that influence someone to commit fraud is. The research used the CFA (Confirmatory Factor Analysis) method and the Extreme Gradient Boosting (XGBoost) method to predict the possibility of fraud. The results revealed that the fraud incident conducted by Relationship Managers (RM) is caused by rationalization factors. The Path diagram of the Second Order CFA fraud risk showed the marketer that the most significant factor loading value was in rationalization, followed by pressure and opportunity. Hence, the results of this research indicated that rationalization had the most significant influence on the fraud risk committed by RM. Therefore It was recommended that the bank or financial institution put its focus more on rationalization matters.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Heri Supriyadi
AU  - Dominicus Savio Priyarsono
AU  - Dominicus Savio Priyarsono
AU  - Trias Andati
PY  - 2023
DA  - 2023/05/15
TI  - Analysis of Internal Fraud in the Microloan Process with Confirmatory Factor Analysis (CFA) and the Extreme Gradient Boosting (XGBoost) Method
BT  - Proceedings of the Business Innovation and Engineering Conference (BIEC 2022)
PB  - Atlantis Press
SP  - 238
EP  - 255
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-144-9_23
DO  - 10.2991/978-94-6463-144-9_23
ID  - Supriyadi2023
ER  -