Assessing Insurance Premium Adequacy Under Macroeconomic Uncertainty: Evidence from Kenya's Insurance Industry

Insurance premium adequacy is central to maintaining solvency and consumer protection, yet in emerging markets it is increasingly challenged by macroeconomic volatility. This study assesses the adequacy of insurance premiums in Kenya under uncertainty by integrating both quantitative econometric models and qualitative reasoning. Annual data from 2015–2024 were drawn from the Insurance Regulatory Authority, Kenya National Bureau of Statistics, and the Central Bank of Kenya. Multiple Linear Regression (MLR) was used to test static relationships, while Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) captured time‑dependent dynamics and produced forecasts for 2025–2027.

Quantitative results show that GDP growth is the most statistically significant driver of premium changes, reflecting the insurance–growth nexus, while inflation and interest rates exhibit expected but statistically weaker effects. ARIMAX modelling improved forecast reliability, generating scenario‑based projections that highlight divergent premium paths under baseline, optimistic, and pessimistic conditions. Qualitatively, the findings align with economic theory: inflation raises claim costs, interest rate shifts alter investment returns and affordability, and GDP growth expands insurance demand. Together, these insights emphasize that premiums are shaped not only by statistical relationships but also by broader economic realities that insurers must anticipate.

The study concludes that premium adequacy requires adaptive, scenario‑based frameworks that integrate both quantitative evidence and qualitative justification. By combining econometric inference with contextual reasoning, this research provides insurers and regulators with practical tools to safeguard solvency and ensure sustainable pricing in Kenya’s volatile economic environment.