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Solvency Determinants of Conventional Life Insurers and Takaful Operators


  • Yakob Rubayah

    (National University of Malaysia)

  • Yusop Zulkornain

    (Al-Faisal University, Jeddah)

  • Radam Alias

    (University Putra Malaysia)

  • Ismail Noriszura

    (National University of Malaysia)


The business of insurance is based on the trust of its policyholders, who expect that their losses will be compensated should the need arise at any time. Thus, sound financial conditions constitute the most important criterion for insurance firms, as well as for takaful operators. Although the policyholder may be the most important source of insurer finance, or a debt holder from an economic point of view through premium payments, the policyholder is not well informed in assessing the financial strength or solvency of the life insurer. Various measures of the solvency of the insurer are used in the industry, such as margin of solvency (MOS), risk based capital (RBC), and claim paying ability (CPA) rating. Unfortunately, none of these can provide information to policyholders on the financial position of the insurer. This is because the MOS and RBC for each insurer is the company's and regulator’s confidential information. However, for the CPA rating, it is limited to insurers who wish to be evaluated, and therefore the assessment is not comprehensive. Because of these shortcomings, this study provides a platform for policyholders to get an idea of the solvency of the insurers/takaful operators. Furthermore, this study identifies factors that affect the solvency of the insurers/takaful operators in Malaysia. Using random effects regression on panel data for 2003-2007, it is determined that investment income, total benefit paid to capital and surplus ratio, financial leverage, and liquidity are significantly related to solvency, in which the investment income has a positive relationship, while the other three have a negative relationship. From the results obtained, the policyholders/consumers can assess the insurers’ financial strength through the solvency determinants of the insurers/takaful operators, even though the actual level of solvency is not known. To some extent, this information can help policyholders/consumers make smarter choices in choosing the insurers/takaful operators

Suggested Citation

  • Yakob Rubayah & Yusop Zulkornain & Radam Alias & Ismail Noriszura, 2012. "Solvency Determinants of Conventional Life Insurers and Takaful Operators," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 6(2), pages 1-25, June.
  • Handle: RePEc:bpj:apjrin:v:6:y:2012:i:2:n:3

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    References listed on IDEAS

    1. Carson, James & Hoyt, Robert, 2000. "Evaluating the risk of life insurer insolvency: implications from the US for the European Union," Journal of Multinational Financial Management, Elsevier, vol. 10(3-4), pages 297-314, December.
    2. Taylor, William E., 1980. "Small sample considerations in estimation from panel data," Journal of Econometrics, Elsevier, vol. 13(2), pages 203-223, June.
    3. Yung-Ming Shiu, 2005. "The determinants of solvency in the United Kingdom life insurance market," Applied Economics Letters, Taylor & Francis Journals, vol. 12(6), pages 339-344.
    4. Brockett, Patrick L. & Cooper, William W. & Golden, Linda L. & Rousseau, John J. & Wang, Yuying, 2004. "Evaluating solvency versus efficiency performance and different forms of organization and marketing in US property--liability insurance companies," European Journal of Operational Research, Elsevier, vol. 154(2), pages 492-514, April.
    5. Giovanni S. F. Bruno, 2005. "Estimation and inference in dynamic unbalanced panel-data models with a small number of individuals," Stata Journal, StataCorp LP, vol. 5(4), pages 473-500, December.
    6. M. Adams & M. Buckle, 2003. "The determinants of corporate financial performance in the Bermuda insurance market," Applied Financial Economics, Taylor & Francis Journals, vol. 13(2), pages 133-143.
    7. Sanchis, A. & Segovia, M.J. & Gil, J.A. & Heras, A. & Vilar, J.L., 2007. "Rough Sets and the role of the monetary policy in financial stability (macroeconomic problem) and the prediction of insolvency in insurance sector (microeconomic problem)," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1554-1573, September.
    8. Patrick L. Brockett & Linda L. Golden & Jaeho Jang & Chuanhou Yang, 2006. "A Comparison of Neural Network, Statistical Methods, and Variable Choice for Life Insurers' Financial Distress Prediction," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 73(3), pages 397-419.
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