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Determinants of Auditors Ability in Fraud Detection

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  • Wahidahwati Wahidahwati
  • Nur Fadjrih Asyik

Abstract

This study aims to examine the effect of auditor experience, auditor ethics, professional skepticism, and auditor personality type on fraud detection. This research was designed using a quantitative approach. Data analysis using multiple linear regression model with spps software. There are several tests carried out before carrying out data analysis. The analysis prerequisite tests include data validity, reliability, normality, multicollinearity, and heteroscedasticity tests. The population and sample in this study were 156 supreme audit boards spread across various regional entities in east java province consisting of 38 city governments and 1 provincial government. The sampling technique used is by using a non-probability sampling approach. The sample in this study amounted to fifty-seven auditors. The results show that auditor experience has a positive and significant effect on fraud detection, auditor ethics has a positive and significant effect on fraud detection, professional skepticism has a positive and significant effect on fraud detection and auditor personality type has a positive and significant effect on fraud detection. The findings of this study are supported by attribution theory and personality type theory.

Suggested Citation

  • Wahidahwati Wahidahwati & Nur Fadjrih Asyik, 2022. "Determinants of Auditors Ability in Fraud Detection," Cogent Business & Management, Taylor & Francis Journals, vol. 9(1), pages 2130165-213, December.
    • Handle: RePEc:taf:oabmxx:v:9:y:2022:i:1:p:2130165
    DOI: 10.1080/23311975.2022.2130165
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    Cited by:

    1. Laura-Andreea Iamandache (Florea), 2022. "Reporting on Errors and Fraud in Financial Audit Missions," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 863-868, Decembrie.
    2. Mehdi Hosseini Chagahi & Niloufar Delfan & Saeed Mohammadi Dashtaki & Behzad Moshiri & Md. Jalil Piran, 2024. "An Innovative Attention-based Ensemble System for Credit Card Fraud Detection," Papers 2410.09069, arXiv.org.

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