Implementing the Z-score to examine the financial stability of insurance companies in Pakistan

Purpose: This study aims to assess simpler and more accessible measures of insurer soundness as alternatives to the complex Solvency II framework. It specifically evaluates the effectiveness of six different Z-score models in measuring the financial stability of insurance companies in Pakistan. Design/methodology/approach: The analysis is based on 296 firm-year observations from 37 insurers over the period 2013–2020. The study applies Ordinary Least Squares (OLS) and System-GMM estimation techniques to examine the predictive ability of various Z-score formulations. Model performance is evaluated using the Root Mean Squared Error (RMSE) criterion to identify the most reliable specification. Findings: The results indicate that the most accurate Z-score model incorporates the present value of Return on Assets (ROA), the equity-to-total assets (EQ/TA) ratio, and the standard deviation of ROA, calculated using a two-year rolling window. This formulation consistently outperforms other variants in predicting financial soundness. The Z-score is shown to be an effective early warning tool for micro-prudential oversight and a practical alternative to complex regulatory risk assessment models. Originality/value: This study contributes to the financial risk literature by adapting Z-score models specifically for the insurance sector. It provides a practical framework for regulators, investors, and academics seeking early indicators of insurer distress, especially in emerging markets. While focused on Pakistan, the methodology offers a foundation for replication in other jurisdictions.