Exploring the Z-score Metrics in Determining the Financial Soundness of Insurance Firms in Nigeria

The Z-score measure, which has traditionally been used as a proxy of individual risk in the banking sector, maybe a useful tool when applied in the insurance sector. This paper compares six different Z-score approaches to examine which one best fits insurance company. The study uses a final data set of 83 firms (listed and unlisted) operating in the Nigeria insurance sector during the period 2015–2022.The study, started by using a root mean squared error (RMSE) criterion to evaluate which of the various mean and standard deviation (SD) estimates that are used to compute the Z-score that best fits the data. The study employed the use of an ordinary least squares (OLS) regression model to estimate and compare the explanatory variables of the six Z-score measures. The study revealed that the best formula for calculating the Z-score of insurance firms is the one that combines the current value of the return on assets (ROA) and capitalization with the standard deviation (SD) of the returns calculated over the full sample period. The study recommended the use of Z-score measure by regulatory supervisors and other relevant stakeholders as a useful early warning indicator of financial distress.