Enhancing enterprise risk management through data analytics: A Strategic Framework for Nigerian Enterprises

Organizations operating in emerging markets such as Nigeria face an increasingly complex risk environment driven by rapid digital transformation, economic volatility, cybersecurity threats, and evolving regulatory demands. Traditional enterprise risk management (ERM) systems, often manual, fragmented, and compliance-oriented, are increasingly inadequate for managing the scale, interdependence, and velocity of contemporary financial, operational, and compliance risks. In response, this study develops a strategic, data analytics–driven framework to enhance ERM practices in Nigerian enterprises. The study adopts a conceptual and exploratory approach grounded in desk research, secondary data synthesis, and industry benchmarking. Established ERM frameworks are integrated with contemporary data analytics capabilities to construct a multi-layered risk management model that spans risk identification, assessment, monitoring, and response. To ensure practical relevance, the framework is contextualized using illustrative Nigerian case evidence from organizations such as Guaranty Trust Bank (GTBank), MTN Nigeria, and Paystack. An industry-level synthesis across financial services, fintech, logistics, and healthcare further demonstrates the framework’s cross-sector applicability. The findings indicate that data analytics substantially enhances ERM effectiveness by enabling predictive risk scoring, anomaly detection, and real-time risk surveillance. Interactive dashboards emerge as a critical mechanism for improving risk visibility, supporting timely managerial decision-making, and strengthening organizational responsiveness. Importantly, the study shows that analytics models localized to Nigeria’s regulatory environment, data infrastructure, and operational constraints outperform generic, Western-centric ERM solutions in terms of feasibility and contextual relevance. This study offers a practical roadmap for Nigerian enterprises seeking to embed analytics within their ERM architectures. Theoretically, it extends the ERM literature by situating analytics-driven risk management within emerging economy contexts and emphasizing localization as a critical determinant of ERM effectiveness.