Fraud detection remains a significant challenge in the public sector, particularly as financial transactions become increasingly complex, necessitating the integration of technology and auditor competencies. Although the Audit Board of the Republic of Indonesia (BPK RI) has implemented Big Data Analytics, effective fraud detection still requires adequate investigative skills and professional judgment. This study aims to examine the influence of Big Data Analytics, Forensic Accounting Skills, and Professional Skepticism on Fraud Detection among auditors at the BPK RI Representative Office of Bengkulu Province. A quantitative approach was employed, utilizing questionnaire data from 45 auditors. The data were analyzed using multiple linear regression with IBM SPSS Statistics. The results indicate that Big Data Analytics has a positive and significant effect on Fraud Detection (β = 0.253; p = 0.023), as do Forensic Accounting Skills (β = 0.358; p = 0.016) and Professional Skepticism (β = 0.357; p = 0.010). Simultaneously, the three independent variables significantly influence Fraud Detection (F = 49.589; p < 0.001), with an adjusted R² of 0.768. Professional Skepticism demonstrates the highest t-statistic among the three variables, indicating its relatively strong contribution to fraud detection in this study. These findings suggest that effective fraud detection in the public sector requires the integration of data analytics technology, forensic accounting competencies, and professional skepticism. Therefore, audit institutions should strengthen the utilization of analytical technology while continuously developing auditors' investigative skills and professional judgment.
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