CONFIDENTIALITY PROTECTION AND MANAGEMENT FRAUD DETECTION IN NIGERIAN BANKING INDUSTRY

Abstract

The Nigerian banking industry has witnessed rapid digital transformation, which, while improving financial inclusion, has increased exposure to sophisticated fraud schemes. This study examined the influence of confidentiality protection on management fraud detection, focusing on the dimensions of Information Access Control (IAC) and Data Encryption & Security Measures (DESM) as independent variables, and Internal Audit & Monitoring (IAM) and Fraud Reporting and Investigation Efficiency (FRIE) as dependent variables. A descriptive survey research design was adopted, targeting 420 staff from selected Deposit Money Banks in Port Harcourt. Data were collected using structured questionnaires and analysed using descriptive statistics, regression analysis, and ANOVA. The findings revealed that both IAC (B = 0.421, p < 0.05) and DESM (B = 0.367, p < 0.05) have a significant positive impact on management fraud detection, with the model explaining 70.9% of the variance (R² = 0.709). This indicates that robust confidentiality measures enhance the effectiveness of fraud monitoring, reduce insider threats, and improve the accuracy of AI-driven detection systems. The study concludes that confidentiality protection and fraud detection are interdependent, forming a holistic defence mechanism essential for safeguarding financial assets and institutional reputation. The study recommends strengthening access controls, adopting advanced encryption protocols, and integrating AI-driven detection tools, conducting regular staff training, and ensuring compliance with the Nigeria Data Protection Act (NDP Act 2023) and Central Bank of Nigeria guidelines. These measures collectively enhance the proactive management of fraud and preserve digital trust in the Nigerian banking sector