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Adoption of AI Tools and Fraud Detection in Selected Microfinance Banks in Lagos
Subject area: Arts, Social Sciences and Humanities · Area of research: AI Adoption, Fraud Detection
Abstract
The rapid rise of fraud in financial institutions continues to threaten stability, erode trust, and undermine long-term sustainability. Microfinance banks (MFBs) in Nigeria, designed to provide financial services to low-income earners and small businesses, are particularly vulnerable due to limited collateral requirements, weak technological infrastructure, and reliance on trust-based relationships. This study examined the adoption of Artificial Intelligence (AI) tools for fraud detection in selected microfinance banks in Lagos, Nigeria. Specifically, it investigated the extent of AI adoption, its effectiveness in enhancing fraud detection, the challenges hindering adoption, and strategies for improvement. The study employed a descriptive survey design with a structured questionnaire administered to 45 respondents drawn from staff of selected MFBs. Data were analyzed using descriptive statistics and regression analysis via SPSS. Findings revealed that although AI adoption in Lagos MFBs remains moderate, AI tools significantly enhance fraud detection accuracy, reduce detection time, and minimize financial losses. However, adoption is constrained by financial costs, inadequate expertise, and weak regulatory frameworks. The test of hypotheses confirmed that AI adoption has a significant positive effect on fraud detection, while challenges exert a negative influence. Respondents strongly endorsed strategies such as infrastructure investment, continuous staff training, and supportive government policies as critical enablers of AI adoption. The study concludes that AI tools are not optional innovations but strategic necessities for mitigating fraud risks in microfinance banking. It recommends coordinated efforts by banks, regulators, and FinTech firms to overcome adoption barriers and strengthen fraud prevention systems.
Keywords
artificial intelligence, fraud detection, microfinance banks, adoption challenges
How to cite this paper
@article{1722837,
author = {Ifeoluwa Francis Taiwo},
title = {Adoption of AI Tools and Fraud Detection in Selected Microfinance Banks in Lagos},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {3},
pages = {192-209},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1722837.pdf},
abstract = {The rapid rise of fraud in financial institutions continues to threaten stability, erode trust, and undermine long-term sustainability. Microfinance banks (MFBs) in Nigeria, designed to provide financial services to low-income earners and small businesses, are particularly vulnerable due to limited collateral requirements, weak technological infrastructure, and reliance on trust-based relationships. This study examined the adoption of Artificial Intelligence (AI) tools for fraud detection in selected microfinance banks in Lagos, Nigeria. Specifically, it investigated the extent of AI adoption, its effectiveness in enhancing fraud detection, the challenges hindering adoption, and strategies for improvement. The study employed a descriptive survey design with a structured questionnaire administered to 45 respondents drawn from staff of selected MFBs. Data were analyzed using descriptive statistics and regression analysis via SPSS. Findings revealed that although AI adoption in Lagos MFBs remains moderate, AI tools significantly enhance fraud detection accuracy, reduce detection time, and minimize financial losses. However, adoption is constrained by financial costs, inadequate expertise, and weak regulatory frameworks. The test of hypotheses confirmed that AI adoption has a significant positive effect on fraud detection, while challenges exert a negative influence. Respondents strongly endorsed strategies such as infrastructure investment, continuous staff training, and supportive government policies as critical enablers of AI adoption. The study concludes that AI tools are not optional innovations but strategic necessities for mitigating fraud risks in microfinance banking. It recommends coordinated efforts by banks, regulators, and FinTech firms to overcome adoption barriers and strengthen fraud prevention systems.},
keywords = {artificial intelligence, fraud detection, microfinance banks, adoption challenges},
month = {September},
}