DATA ANALYTICS AND RISK BASED SUPERVISION IN THE NIGERIAN INSURANCE INDUSTRY: AN EMPIRICAL ASSESSMENT

Abstract

The objective of this study was to evaluate the effects of data analytics in supporting risk-based supervision (RBS) within the Nigerian insurance industry. Specifically, the study examined the impact of risk-based supervision on insurance company performance, assessed the role of analytical skills in implementing RBS, and explored the relationship between the adoption of data analytics and the implementation of RBS. A descriptive survey research design was adopted, utilizing a structured questionnaire to gather primary data from 277 respondents across six selected insurance companies in Lagos State through the administration of copies of questionnaires for the study. The data were analyzed using descriptive and inferential statistics, particularly regression analysis, with the aid of SPSS version 25. Findings revealed that risk-based supervision has a statistically significant positive effect on insurance company performance. Analytical skills were also found to significantly influence the successful implementation of risk-based supervision. Furthermore, the study established a strong, positive, and statistically significant relationship between the adoption of data analytics and risk-based supervision implementation. The study concludes that data analytics, supported by strong analytical skills and effective risk-based strategies, significantly underpinned by strong analytical capabilities and well-structured risk based framework enhances the performance and regulatory compliance of insurance companies in Nigeria. It is recommended that regulatory bodies and insurance firms should intensify the implementation of RBS through deepening internal analytical capabilities and investing in data analytics infrastructure. These measures, within Nigeria’s regulatory context, will enable data-driven decision-making and more robust supervision, ultimately promoting stability and growth in the insurance sector.