MODELING FRAUDS IN NIGERIA BANKS A CASE STUDY OF FIRST BANK
Abstract
ABSTRACT
The persistent occurrence of fraud in the banking sector poses significant challenges to economic stability and institutional integrity. This study focuses on modeling fraud in Nigerian banks, with a specific case study of First Bank Nigeria. The research aims to analyze patterns and factors influencing fraud occurrences from 2009 to 2023, utilizing data from First Bank’s annual reports, the Nigeria Deposit Insurance Corporation (NDIC), the Nigeria Inter-Bank Settlement System (NIBSS), and the Central Bank of Nigeria (CBN).
The study employs both Poisson regression and Negative binomial regression model to estimate the frequency of fraud incidents, using the number of fraud cases as the dependent variable and factors such as the total volume of transactions, amount lost, and actual loss proportion as independent variables. Maximum Likelihood Estimation (MLE) is used for parameter estimation, while model diagnostics, including deviance, Pearson Chi-square tests, and residual analysis, are conducted to assess model adequacy.
Findings highlight the role of both economic conditions and internal control mechanisms in shaping fraud dynamics within the bank. The results are intended to aid policymakers and bank management in devising more robust strategies for fraud prevention and control.
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