An evaluation of the financial soundness of insurance firms in the Amman Stock Exchange
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Author(s)Hussein Mohammad SalamehLink to ORCID Index: https://orcid.org/0000-0001-6893-1862
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DOIhttp://dx.doi.org/10.21511/ins.13(1).2022.02
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Article InfoVolume 13 2022, Issue #1, pp. 11-20
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Financial soundness of insurance firms within a country tends to heavily affect its financial environment. This study will further assess the relationship between both factors with the support of a special model to test the financial soundness of insurance companies. The model could be utilized as an indicator of the stabilization of a country’s financial environment; this is done by testing the insurance companies’ falls. The methodology used was discriminant regression on the Amman Stock Exchange (ASE) to test 12 indicators that were derived from six CARMEL model parameters. The six tested parameters were: capital adequacy, asset quality, reinsurance and actuarial issues, management efficiency, earnings and profitability, and liquidity. The results have shown that 10 out of 12 indicators are significant factors. Additionally, the study proved that the CARMEL model is an applicable model to test the financial soundness of ASE insurance companies, the possibility of detecting a deviation between the actual and expected performance was barely minimum. The effect of deviation was present in eight firms out of 19, three of which were affected by the type II error (riskier deviation). The study concluded that the CARMEL model is a significant model, and the insurance firms that follow the Jordan Insurance Federation (JIF) requirements are financially sound.
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JEL Classification (Paper profile tab)G22, G32, C52
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References29
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Tables7
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Figures0
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- Table 1. Descriptive statistics
- Table 2. Test of means’ equality
- Table 3. Correlation matrix
- Table 4. Covariance matrices equality
- Table 5. Canonical discriminant functions
- Table 6. Classification statistics results
- Table 7. Performance vs. predicted performance
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- Ahmed, R., & Sarkar, S. (2019). Measurement of Financial Soundness of Life Insurance Companies in Bangladesh: An Empirical Study. Business Review – A Journal of Business Administration Discipline, 14(1), 29-43.
- Ansari, V., & Fola, W. (2014). Financial Soundness and Performance of Life Insurance Companies in India. International Journal of Research, 1(8), 224-253.
- Bawa, S., & Verma, N. (2017). Conducting Financial Analysis of the Indian Reinsurer-GIC Re. Pacific Business Review International, 10(3), 113-120.
- Chakraborty, J. & Sengupta, P. (2014). Financial soundness in Indian insurance sector: A comparison between two leading life insurers. 2014 2nd International Conference on Business and Information Management (ICBIM).
- Chen, R., & Wong, K. (2004) The Determinants of Financial Health of Asian Insurance Companies. The Journal of Risk and Insurance, 71(3), 469-499.
- Dar, S., & Bhat, J. (2015). A Comparative Evaluation of Financial Performance and Soundness of Selected Public and Private Life Insurers in India. Pacific Business Review International, 7(10), 55-64.
- Darzi, T. A. (2012). Financial performance of insurance industry in post liberalization era in India (Ph.D. Thesis).
- Das, U., Davis, N., & Podpiera, R. (2003). Insurance and Issues in Financial Soundness (IMF Working Papers No. WP/03/138). International Monetary Fund.
- Graham Value. (2003). Public-Utilities and Financial Enterprises.
- Hussain, I. (2015). Macro Economy and Profitability of Insurance Companies: A Post Crisis Scenario on Pakistan. Pakistan Business Review.
- Jordan Insurance Federation (JIF). (n.d.) Website.
- Kramer, B. (1996). An ordered logit model for the evaluation of Dutch non-life insurance companies. De Economist, 144, 79-91.
- Kugler, M., & Ofoghi, R. (2005). Does Insurance Promote Economic Growth? Evidence from the UK (Working Paper).
- Kumar, P., & Ghimire, R. (2013). Testing of Financial Performance of Nepalese Life Insurance Companies by CARMELS Parameters. Journal of Business and Management, 2-15.
- Lee, H., & Lee, C. (2011). Determinants of property-liability insurer retention: Evidence from Taiwan insurance industry. African Journal of Business Management, 5(32), 12543-12550.
- Morara, K. & Sibindi, A. (2021). Determinants of Financial Performance of Insurance Companies: Empirical Evidence Using Kenyan Data. Journal of Risk Financial Management, 14(12), 566.
- Moreno, I., Parrado-Martinez, P., & Trujillo-Ponce, A. (2021). Using the Z-score to analyze the financial soundness of insurance firms. European Journal of Management and Business Economics, 31(1), 22-39.
- Patel, K. & Patel, P. (2020). Performance of Selected Life Insurance Companies – Comparative Analysis. International Journal of Finance and Banking Research, 7(2), 51-57.
- Puławska, K. (2021). Financial Stability of European Insurance Companies during the COVID-19 Pandemic. Journal of Risk Financial Management, 14(6), 266.
- Qatar Central Bank. (2017). Qatar General Insurance & Reinsurance Company Q.P.S.C (Corporate Governance Report for 2017).
- Salameh, H. (2021). Failure threats of insurance companies: A case study of financial environments of Jordan. Investment Management and Financial Innovations, 18(3), 113-126.
- Shim, J. (2017). An Investigation of Market Conentration and Financial Stability in Property – Liability Insurance Industry. The Journal of Risk and Insurance, 82(2), 567-597.
- Simpson, S., & Damoah, O. (2009). An Evaluation of Financial Health of Non-Life Insurance Companies from Developing Countries: The Case of Ghana.
- Sliwinski, A., Michalski, T., & Roszkiewicz, M. (2013). Demand for Life Insurance – An Empirical Analysis in the Case of Poland. The Geneva Papers on Risk and Insurance – Issues and Practice, 38, 62-87.
- Smajla, N. (2014). Measuring Financial Soundness of Insurance Companies by Using CARMELS Model – Case of Croatia. Interdisciplinary Management Research, 10, 600-609.
- Sokic, M. (2019). Analysis of Insurance Industry CARMEL Indicators in REPUBLIC OF SERBIA.
- Surya, M., & Sudha, B. (2020). Insurance Financial Soundness Indicator – Carmel Model. International Journal of Advanced Science & Technology, 29(1), 1234-1242.
- Widati, T., & Anas, E. (2019). Comparing Three Models to Evaluate Financial Soundness of Life Insurance Companies in Indonesia. Proceedings of the 2nd International Conference on Inclusive Business in the Changing World (ICIB) (pp. 568-576). Jakarta, Indonesia.
- Yakob, R., Yusop, Z., Radam, A., & Ismail, N. (2021). Camel Rating Approach to Assess the Insurance Operators Financial Strength. Jurnal Ekonomi Malaysia, 46(2), 3-15.
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Failure threats of insurance companies: A case study of financial environments of Jordan
Hussein Mohammad Salameh
doi: http://dx.doi.org/10.21511/imfi.18(3).2021.11
Investment Management and Financial Innovations Volume 18, 2021 Issue #3 pp. 113-126 Views: 766 Downloads: 382 TO CITE АНОТАЦІЯInsurance firms are known to have unique financial failure characteristics that affect the financial environment of the countries. Therefore, the purpose of this study is to assess the validity of the model used in predicting the financial failures of insurance companies. The model is believed to help in stabilizing the financial environment of the countries by predicting any collapses in the insurance sector. A discriminate regression technique was used to test 28 indicators chosen from 11 financial failure model parameters. 11 parameters of the model are the following: solvency, profitability, operational capabilities, structural soundness, capital expansion capacity, capital adequacy, reinsurance and actuarial issues, management soundness, capital expansion capacity, earnings and profitability, and liquidity. The results of the study proved that 22 variables from 11 parameters were significant; the study also validated the use of the financial failure model as a stable predictor of the financial failure of ASE insurance firms. The stability of the insurance industry is interpreted through the minimum deviation between the real and measured performances. The deviation was present in 3 out of 95 observations, and it affected only 3 firms out of 19, 1 firm out of 3 turned out to be affected by the risker deviation which is the type II error distorted observation. To conclude, the study by mentioning that insurance firms are not threatened by failure or distress and the financial failure model is a valid prediction model.
