Influence of big data competencies and self-efficacy on detection of financial statement fraud on internal auditors in Indonesia / Novy Silvia Dewi ... [et al.]

Detection of financial statement fraud is important in maintaining the integrity and reliability of a company’s financial information. Internal auditors have the responsibility to detect fraud in the company’s financial statements. This study aimed to test whether the existence of big data competencies can help internal auditors in the detection of financial statement fraud. This study also examined whether psychological factors such as self-efficacy can affect internal auditors in the detection of financial statement fraud. The research method used was the quantitative method. The research focused on internal auditors who employed in Indonesian companies. Data collection used questionnaire with 230 samples and analyzed using regression analysis using SmartPLS software. The results showed that big data competencies had a positive and significant effect on self-efficacy. The ability to analyze big data competencies is crucial role in detecting financial statement fraud, and individuals’ confidence in their skills also had a positive impact on fraud detection. Additionally, selfefficacy served as a significant mediator between big data competencies and the detection of financial statement fraud. This research has significant implications for practitioners and organizations in Indonesia in the context of developing strategies to improve the ability of internal auditors to detect fraudulent financial reports.