Data-Driven Innovation and Financial Fraud Mitigation of the Manufacturing Firms in Nigeria

This study examined the effect of data-driven innovation on financial fraud mitigation in listed manufacturing firms in Nigeria. Specifically, the study assessed the impact of predictive analytics and big data infrastructure on financial fraud mitigation across eighteen manufacturing companies listed on the Nigerian Exchange Group (NGX) over a ten-year period from 2016 to 2025. The study adopted a quantitative research approach using secondary data drawn from the annual reports and financial statements of the sampled firms. Panel data regression analysis was employed as the primary analytical technique, Descriptive statistics with the Fixed Effects model selected, following the Hausman Specification Test. Diagnostic tests confirmed that all required statistical assumptions were satisfied. The correlation analysis revealed strong positive relationships between predictive analytics, big data infrastructure, and financial fraud mitigation. The regression results showed that predictive analytics has a significant positive impact on financial fraud mitigation (β = 0.487, p = 0.000), and that big data infrastructure also has a significant positive influence on financial fraud mitigation (β = 0.432, p = 0.003). Both null hypotheses were accordingly rejected. The study concludes that data-driven innovation is a powerful tool for reducing financial fraud in the Nigerian manufacturing sector and recommends that listed manufacturing firms prioritize investment in analytics tools and technology infrastructure as a core component of their fraud management strategies.