Financial reporting fraud detection using machine learning pipeline
Nurfarizan Mazhani Mahmud, Rahayu Abdul Rahman

Universiti Teknologi MARA, Kampus Tapah

Abstract

This research aims to investigate the effectiveness of machine learning in predicting financial reporting fraud among listed companies in Malaysia. Ten financial ratios are used as fraud risk indicator to predict financial reporting fraud. The samples of 20 fraudulent firms and 20 non fraudulent firms which financial data are available from 2010-2018 are used using match pair in this study. The findings reveal that machine learning is effective in predicting both fraudulent and non fraudulent firms compared to traditional approach of financial reporting fraud detection.

Keywords: Financial reporting fraud, fraud detection, machine learning,

Topic: International Conference of Islamic Economic and Financial Inclusion

Link: https://ifory.id/abstract-plain/F8EuACqvGmXU

Web Format | Corresponding Author (Nurfarizan mazhani Mahmud)