Artificial Intelligence in Fintech and Its Implications For Fraud Detection in Accounting Systems

Promise Ezinne Eleke, John Ogwo Madukwe

Abstract

Financial technology (FinTech) and artificial intelligence (AI) have transformed fraud detection in financial systems. Financial institutions increasingly use AI to detect fraud; however, empirical research on its impact on fraud-detection efficiency in developing economies is limited. The study explores how AI use in FinTech systems affects fraud detection effectiveness, considering firm size, regulatory compliance, technology readiness, internal control systems, and cybersecurity infrastructure. This study employs a panel dataset of 40 financial institutions (FIs) that operate in the Nigerian FinTech market from 2019 to 2023. The researchers used the fixed-effects estimator after conducting the Hausman test. The findings also show that the use of AI has a significant positive effect on the efficiency of fraud detection (β = 0.412, p < 0.01); internal control systems (β = 0.238, p < 0.01) and cybersecurity infrastructure (β = 0.196, p < 0.05) also support fraud detection results. The model has an R² of 0.614, indicating that it explains 61.4% of the variance in fraud detection efficiency. The results align with the Routine Activity Theory and the Technology Acceptance Model as valuable theoretical frameworks for understanding AI-driven fraud prevention in financial institutions. The study suggests the following strategies to boost the integrity of accounting systems in emerging FinTech markets: strategic investment in AI systems, strengthening the cybersecurity architecture, harmonising regulations, and building institutional capacity.

10.22178/pos.130-9


Keywords


Artificial Intelligence; FinTech; Fraud Detection Efficiency; Accounting Systems; Panel Regression; Nigeria

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References


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Copyright (c) 2026 Promise Ezinne Eleke, John Ogwo Madukwe

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