Predicting Financial Failure in Algerian Public Insurance Companies Using the Kida Model - Morkane Mohamed El Bachir; Khaled Mili; Ismail Bengana; Imane Benaouali (Journal of Applied Data Sciences, 2024)
This study evaluates the effectiveness of financial ratios in predicting the financial health of Algerian public insurance companies using the Kida model, a robust tool for identifying potential financial failure and bankruptcy risks. The primary objective is to assess the predictive power of the Kida model for early detection of financial failure. The research employs a case study approach, analyzing financial statements from three major public insurance companies in Algeria (SAA, CAAR, CAAT) over the period from 2015 to 2021. Key contributions include a comprehensive analysis of financial ratios such as profitability, solvency, liquidity, and management efficiency, and their integration into the Kida model. The methodology involves a detailed examination of financial data, application of the Kida model, and interpretation of the financial failure index. Our findings reveal that the Kida model accurately predicts financial failure risks, with all values of the financial failure index being negative, indicating potential vulnerability. The study underscores the importance of early detection systems and proactive financial management to ensure stability and sustainability in the insurance sector. The results have significant implications for policymakers and stakeholders, emphasizing the need for tailored financial failure prediction models for the Algerian insurance industry. Future research could expand on this work by incorporating real-world data and exploring other predictive models to enhance accuracy and reliability.