THE USE OF AI IN FRAUD DETECTION AND FINANCIAL PERFORMANCE OF AGRO-BASED MANUFACTURING FIRMS IN NIGERIA.

Abstract

This study investigates how integrating Artificial Intelligence (AI) into corporate internal control frameworks affects the financial performance of listed agro-based manufacturing companies in Nigeria. These firms are particularly vulnerable to financial leakages, such as inventory diversion and invoice fraud, because they operate across decentralized and logistically exposed supply chains stretching from rural farms to urban processing plants. Utilizing a concurrent triangulation mixed-methods research design, this paper combines primary survey data from 132 accounting and IT audit professionals with an eight-year panel dataset (2018–2025) derived from the audited reports of the three major listed agro-allied enterprises on the Nigerian Exchange: Okomu Oil Palm Company Plc, Presco Plc, and FTN Cocoa Processors Plc. The study operationalizes AI fraud detection using three core metrics—Machine Learning Adoption (MLA), Automated Auditing Systems (AAS), and Systems Integration Level (SIL)—and measures their impact against Return on Equity (ROE), Return on Assets (ROA), and Net Profit Margin (NPM) using Ordinary Least Squares (OLS) panel regression. The empirical findings show that Machine Learning Adoption significantly enhances ROE (β=0.142, p<0.05) by protecting equity funds from administrative misstatements. Automated Auditing frameworks show a strong positive effect on ROA (β=0.524, p<0.01) by introducing continuous transactional verifications that prevent warehouse leakages. Concurrently, enterprise-wide Systems Integration unifies operational visibility and expands NPM (β=0.231, p<0.01) by cutting out administrative waste and duplicate billing. Ultimately, transitioning to algorithmic AI compliance shifts internal controls from reactive post-mortems into proactive asset protection mechanisms. The study recommends that regulatory bodies modernize local corporate governance codes to actively incentivize digital transitions across the manufacturing sector.