EFFECT OF FINANCIAL METRICS ON FRAUD DETECTION IN NIGERIAN COMMERCIAL BANKS

Abstract

This study investigates the effect of financial metrics on fraud detection in Nigerian deposit money banks. The analysis employs yearly time series data spanning from 2007 to 2022, acquired from the Exchange Group PLC. Descriptive statistics, panel unit root tests, Hausman tests, and Panel Ordinary Least Squares (OLS) procedures were used at a 95% confidence interval. The study utilized secondary data sourced from the Exchange Group PLC database. The R-squared (0.564390) and Adjusted R-squared (0.540629) values indicate that the models have strong explanatory power. The results show that all variables are stationary at their levels (I(0)). The primary factors influencing fraud detection among deposit money banks in Nigeria are revenue growth, net interest margin, and earnings per share. It was recommended that banks should, Implement effective fraud detection systems that can handle increased complexity and scale of operations, and regularly update them, leveraging blockchain technology for decentralized fraud detection as it relates to Revenue Growth Rate of banks. Maintain a healthy Net Interest Margin through effective risk management practices and internal controls, and utilize this strength to invest in fraud detection measures, introducing incentive programs to encourage employee involvement in fraud detection. Conduct regular financial reviews and audits to ensure accurate earnings reporting and detect fraud, utilizing AI-powered tools for earnings analysis to identify anomalies and potential fraud. Prioritize prudent lending practices and effective risk management to maintain financial stability, implementing dynamic adjustments to the debt- to-equity ratio in response to changes in fraud detection needs.

KEYWORDS: Financial Metrics, Fraud, Deposit Money Banks, Fraud Detection, Nigeria