Issue
Date Log

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Copyright
Upon acceptance of an article, authors transfer copyright to the JIEB as part of a journal publishing agreement, but authors still have the right to share their article for personal use, internal institutional use, and for any use permitted under the CC BY-SA license
Open Access
Articles are freely available to the public without any subscription with permitted reuse. For open access articles, permitted third party (re)use is defined by the following Creative Commons user licenses: Creative Commons Attribution (CC BY-SA).
Rebuild the Trust: Predicting the Financial Well-Being of Indonesian Insurers
Corresponding Author(s) : Endang Dwi Astuti
Journal of Indonesian Economy and Business,
Vol 40 No 2 (2025): May
Abstract
Introduction/Main Objectives: The emerging markets’ economic growth relies on stable insurance sectors, which mitigate risk, maintain liquidity, and manage profitability for sustainable growth. This paper aims to examine the financial well-being prediction model using logit regression for Indonesian life and general insurance companies one year and two years before a failure event. Background Problems: The rise of insurance failures erodes people's trust, especially in Indonesia where financial literacy is still an ongoing issue. Novelty: Numerous studies examine the methodology for predicting insurance failure, but some of these procedures have statistical limitations or do not address the unique issue in the emerging markets’ setting. Research Methods: This study employs logistic regression as its methodology and focuses on the life and general insurers operating in Indonesia between 2012 and 2020, using publicly available data. Finding/Results: This study finds the financial well-being of general insurance companies is dependent on their investment performance, profitability, liquidity, change in asset mix, premiums, and surplus growth, leverage, the inflation rate, and change in money reserves. While firm size, the operating margin, premium growth, liquidity change in the asset mix, the combined ratio of loss and expense ratios, surplus growth, and leverage are the key leading indicators of life insurers’ insolvency. Conclusion: Firms with poor investment performance, low premium growth, and extreme levels of leverage are more likely to be insolvent. This study suggests that local authorities should regulate insurance companies' investment strategies, moderate their asset mix changes, and implement sound risk management systems to mitigate performance fluctuations.
Keywords
Download Citation
Endnote/Zotero/Mendeley (RIS)BibTeX
- Abdu, E. (2022). Financial distress situation of financial sectors in Ethiopia: A review paper. Cogent Economics & Finance, 10(1). https://doi.org/10.1080/23322039.2021.1996020
- Altman, E. I., Iwanicz-Drozdowska, M., Laitinen, E. K., & Suvas, A. (2020). A race for long horizon bankruptcy prediction. Applied Economics, 52(37), 4092-4111.
- Ambrose, J. M., & Carroll, A. M. (1994). Using Best's ratings in life insurer insolvency prediction. Journal of Risk and Insurance, 61(2), 317-327.
- Amoa-Gyarteng, K. (2021). Corporate financial distress: The impact of profitability, liquidity, asset productivity, activity and solvency. Journal of Accounting, Business And Management (JABM), 28(2), 104-115. doi:10.31966/jabminternational.v28i2.447
- BarNiv, R., & Hershbarger, R. A. (1990). Classifying financial distress in the life insurance industry. Journal of Risk and Insurance, 57(1), 110-136.
- Brockett, P. L., Cooper, W. W., Golden, L. L., & Pitaktong, U. (1994). A neural network method for obtaining an early warning of insurer insolvency. Journal of Risk and Insurance, 61(3), 402-424.
- Browne, M. J., & Hoyt, R. E. (1995). Economic and market predictors of insolvencies in the property-liability insurance industry. Journal of Risk and Insurance, 62(2), 309-327.
- Carson, J. M., & Hoyt, R. E. (1995). Life insurer financial distress: classification models and empirical evidence. Journal of Risk and Insurance, 62(4), 764-775.
- Chen, R., & Wong, K. A. (2004). The determinants of financial health of Asian insurance companies. Journal of risk and insurance, 71(3), 469-499.
- Cummins, J. D., Harrington, S. E., & Klein, R. (1995). Insolvency experience, risk-based capital, and prompt corrective action in property-liability insurance. Journal of Banking & Finance, 19(3-4), 511-527.
- de Bandt, O., & Overton, G. (2022). Why do insurers fail? A comparison of life and nonlife insurance companies from an international database. Journal of Risk and Insurance, 89(4), 871-905.
- Dewi, T. T. C. (2017). Effect of change in surplus ratio, incurred loss ratio, liquidity ratio, premium growth ratio, size and risk based capital to predict the possibilities of financial distress: The case of Indonesian non-life insurance listed in Indonesia insurance directory. Advanced Science Letters, 23(8), 7285-7288.
- Gregova, E., Valaskova, K., Adamko, P., Tumpach, M., & Jaros, J. (2020). Predicting financial distress of slovak enterprises: Comparison of selected traditional and learning algorithms methods. Sustainability, 12(10), 3954.
- Harrington, S. E., & Nelson, J. M. (1986). A regression-based methodology for solvency surveillance in the property-liability insurance industry. Journal of Risk and Insurance, 53(4) 583-605.
- Harris, M., & Raviv, A. (1990). Capital structure and the informational role of debt. The journal of finance, 45(2), 321-349.
- Hsiao, S. H., & Whang, T. J. (2009). A study of financial insolvency prediction model for life insurers. Expert Systems with Applications, 36(3), 6100-6107.
- Isayas, Y.N. (2021). Financial distress and its determinants: Evidence from insurance companies in Ethiopia, Cogent Business & Management, 8(1).
- Jobst, A. A. (2014). Systemic Risk in the insurance sector: A review of current assessment approaches. The Geneva Papers on Risk and Insurance. Issues and Practice, 39(3), 440–470. http://www.jstor.org/stable/24736576
- Joo, B. A. (2013). Analysis of financial stability of Indian non-life insurance companies. Asian Journal of Finance & Accounting, 5(1), 306.
- Kamaluddin, A., Ishak, N., & Mohammed, N. F. (2019). Financial distress prediction through cash flow ratios analysis. International Journal of Financial Research, 10(3), 63-76.
- Kebede, T. N., Tesfaye, G. D., & Erana, O. T. (2024). Determinants of financial distress: evidence from insurance companies in Ethiopia. Journal of Innovation and Entre¬pre¬neurship, 13(1), 17. https://doi.org/10.1186/s13731-024-00369-5
- Kessler, D., de Montchalin, A., Thimann, C., Hufeld, F., & Koijen, S. J. (2017). The macroeconomic role of insurance. The Economics, Regulation, and Systemic Risk of Insurance Markets, 2, 20-54.
- Kim, Y. D., Anderson, D. R., Amburgey, T. L., & Hickman, J. C. (1995). The use of event history analysis to examine insurer insolvencies. Journal of Risk and Insurance, 62(1), 94-110.
- Kliestik, T., Valaskova, K., Lazaroiu, G., Kovacova, M., & Vrbka, J. (2020). Remain¬ing financially healthy and competitive: The role of financial predictors. Journal of Competitiveness, (1).
- Kramer, B. (1996). An ordered logit model for the evaluation of Dutch non-life insurance companies. De Economist, 144(1), 79-91.
- Kristanti, F.T, Rahayu, S., & Huda, A.N. (2015). The determinant of financial distress on Indonesian family firm. Procedia – Social and Behavioral Sciences, 219, 440-447.
- Kristanti, F.T., Syafia, N.V.M., Arifin, Z. (2021). An early warning system of life insurance companies distress in Indonesia. Multicultural Education, 7(1).
- Kulustayeva, A., Jondelbayeva, A., Nurmagam¬betova, A., Dossayeva, A., Bikteubayeva, A. (2020). Financial data reporting analysis of the factors influencing on profitability for insurance companies. Entrepreneurship and Sustainability Issues, 7(3), 2394-2406.
- Lantara, I.W.K. (2010). A survey on the use of derivatives in Indonesia. Gadjah Mada International Journal of Business, 12(3), 295-323
- Lee, S. H., & Urrutia, J. L. (1996). Analysis and prediction of insolvency in the property-liability insurance industry: A comparison of logit and hazard models. Journal of Risk and insurance, 63(1) 121-130.
- Leadbetter, D., Dibra, S. (2008). Why insurers fail: The dynamics of property and casualty insurance insolvency in Canada. The Geneva Papers on Risk and Insurance – Issues and Practice, 33, 464-488
- Lukason, O., & Andresson, A. (2019). Tax arrears versus financial ratios in bankruptcy prediction. Journal of Risk and Financial Management, 12(4), 187.
- MacKie‐Mason, J. K. (1990). Do taxes affect corporate financing decisions? The Journal of Finance, 45(5), 1471-1493.
- McDonald, J. B. (1993). Predicting insurance insolvency using generalized qualitative response models. Workers’ Compensation Insurance: Claim Costs, Prices, and Regulation, 223-241.
- Morara, K., Sibindi, A.B. (2021). Determinants of financial performance of insurance companies: Empirical evidence using Kenyan data. Journal of Risk and Financial Management, 14(566).
- Mselmi, N., Lahiani, A., & Hamza, T. (2017). Financial distress prediction: The case of French small and medium-sized firms. International Review of Financial Analysis, 50, 67-80.
- Muizzuddin, Tandelilin, E., Hanafi, M.M., Setiyono, B. (2021). Does institutional quality matter in the relationship between competition and bank stability? Evidence from Asia. Journal of Indonesian Economy and Business, 36(3), 283-301.
- Nustini, Y., & Amiruddin, A. R. (2019). Altman model for measuring financial distress: Comparative analysis between sharia and conventional insurance companies. Journal of Contemporary Accounting, 161-172.
- Oktavia, O., Siregar, S.V., Wardhani, R., Rahayu, N. (2019). The effects of financial derivatives on earnings management and market mispricing. Gadjah Mada Interna¬tional Journal of Business, 21(3), 289-307.
- Outreville, J. F. (2013). The relationship bet-ween insurance and economic development: 85 empirical papers for a review of the literature. Risk Management and Insurance Review, 16(1), 71-122.
- Ozili, P.K. (2023). The acceptable R-square in empirical modelling for social science research. Munich Personal RePEc Archive, 115769.
- Rahman, A., Belas, J., Kliestik, T., & Tyll, L. (2017). Collateral requirements for SME loans: empirical evidence from the Visegrad countries. Journal of Business Economics and Management, 18(4), 650-675.
- Rubio-Misas, M. (2020). Ownership structure and financial stability: Evidence from Takaful and conventional insurance firms. Pacific-Basin Finance Journal, 62, 101355.
- Santoso, S.B., Astuti, H.J., Sayekti, L.M. (2020). The effect of claim expense, liquidity, risk-based capital, company size, debt to equity, and debt to asset on profitability in Indonesian Islamic insurance companies. Proceedings of the 2nd International Conference of Business, Accounting, and Economics, ICBAE 2020.
- Septina, F. (2022). Determinant of financial performance for general insurance compa¬nies in indonesia. Jurnal Khatulistiwa Informatika, 6(1), 88-97.
- Shaked, I. (1985). Measuring prospective probabilities of insolvency: An application to the life insurance industry. Journal of Risk and Insurance, 52(1), 59-80.
- Soto‐Simeone, A., Sirén, C., & Antretter, T. (2020). New venture survival: A review and extension. International Journal of Manage¬ment Reviews, 22(4), 378-407.
- Svabova, L., Michalkova, L., Durica, M., & Nica, E. (2020). Business failure prediction for Slovak small and medium-sized companies. Sustainability, 12(11), 4572.
- Tsvetkova, L., Yurieva, T., Orlaniuk-Malitskaia, L., & Plakhova, T. (2019). Financial intermediary and insurance companies: Assessing financial stability. Montenegrin Journal of Economics, 15(3), 189-204.
- Tumbelaka, I., Dimasqy, D., Yusgiantoro, I. B., & Mardiyyah, M. M. (2021). Does investment portfolio affect insurance failure? Evidence from Indonesia. Working Paper.
- Vadlamannati, K. C. (2008). Do insurance sector growth and reforms affect economic development? Empirical evidence from India. Margin: The Journal of Applied Economic Research, 2(1), 43-86.
- Ul Hassan, E., Zainuddin, Z., & Nordin, S. (2017). A review of financial distress prediction models: logistic regression and multivariate discriminant analysis. Indian-Pacific Journal of Accounting and Finance, 1(3), 13-23.
- Valaskova, K., Kliestik, T., & Kovacova, M. (2018). Management of financial risks in Slovak enterprises using regression analysis. Oeconomia Copernicana, 9(1), 105-121.
- Yonas, N. I. (2021). Financial distress and its determinants: Evidence from insurance companies in Ethiopia. Cogent Business & Management. https://doi.org/10.1080/23311975.2021.1951110
- Yosha, O. (1995). Information disclosure costs and the choice of financing source. Journal of Financial Intermediation, 4(1), 3-20.
- Zizi, Y., Jamali-Alaoui, A., El Goumi, B., Oudgou, M., & El Moudden, A. (2021). An optimal model of financial distress prediction: A comparative study between neural networks and logistic regression. Risks, 9(11), 200.
- Zelie, E.M. (2019). Determinants of financial distress in case of insurance companies in Ethiopia. Research Journal of Finance and Accounting, 10(15).