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Journal articles on the topic 'Non-life insurance'

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Published: 4 June 2021

Last updated: 25 July 2025

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1

Carroll, Patrick, and E. Straub. "Non-Life Insurance Mathematics." Journal of the Royal Statistical Society. Series A (Statistics in Society) 153, no. 2 (1990): 262. http://dx.doi.org/10.2307/2982815.

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2

Drissi, Ramzi, and Emtinan Alsuhaibani. "Asymmetric effects of life and non-life insurance on economic growth in Saudi Arabia: A nonlinear analysis." Insurance Markets and Companies 15, no. 2 (2024): 26–34. http://dx.doi.org/10.21511/ins.15(2).2024.03.

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This paper explores the asymmetric effects of life and non-life insurance on economic growth in Saudi Arabia. Quarterly data on insurance penetration rates and GDP growth from 2009 to 2022, obtained from the Global Economy, Saudi Arabian Monetary Authority, and World Bank databases, are utilized. A nonlinear autoregressive distributed lag (NARDL) model is employed to examine the relationships between insurance and growth. The results reveal a significant and asymmetric relationship between life insurance penetration and GDP growth. Specifically, a 1% increase in life insurance penetration is a

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3

Abusharbeh, Mohammed, Sana’ Atari, and Assem Atallah. "The determinants of non-life insurance spending: Evidence from Arab economies." Insurance Markets and Companies 16, no. 1 (2025): 54–63. https://doi.org/10.21511/ins.16(1).2025.05.

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Non-life insurance has grown in developing countries over the past decade, despite challenges and large differences in premiums across Arab countries. This study investigates the effect of cultural factors on non-life insurance spending in Arab countries using panel data covering the period from 2010 to 2023. Eight independent variables were employed. They are uncertainty avoidance, individualism, power distance, masculinity, long-term orientation, indulgence, income per capita and interest rate. The results of the study prove that uncertainty avoidance positively influences spending on non-li

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4

Witkowska, Justyna. "The Life and Non-Life Insurance Market in the European Union." Olsztyn Economic Journal 18, no. 2 (2023): 157–70. http://dx.doi.org/10.31648/oej.10290.

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The article discussed on the situation of the life and non-life insurance market in the European Union as seen at the end of 2022. The market analysis was based on data derived from the European Insurance and Occupational Pensions Authority (EIOPA) and the Organization for Economic Cooperation and Development (OECD) and included such factors as the number of insurers, the division into life insurance and non-life insurance, and the key market indicators (written premium, density and penetration rates, and concentration index). The collected data shows the life and non-life insurance market in

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5

Schmidli, Hanspeter. "Optimisation in Non-Life Insurance." Stochastic Models 22, no. 4 (2006): 689–722. http://dx.doi.org/10.1080/15326340600878420.

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6

Ms., Gurjeet Kaur. "FINANCIAL PERFORMANCE OF INDIAN INSURANCE COMPANIES USING RATIO ANALYSIS." International Journal of Marketing & Financial Management 2, no. 9 (2014): 16–20. https://doi.org/10.5281/zenodo.10806927.

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<strong>Abstract</strong> <em>The objective of this paper is to compare the financial performance of public and private life and non-life insurance companies with the help of solvency ratio. The major life insurance companies are Life Insurance Corporation of India, Bajaj Allianz Life Insurance Company, HDFC Standard Life Insurance Company, ICICI Prudential Life Insurance Company and Birla Sunlife Insurance Company Limited. The major non-life insurance companies are National Insurance Company Limited,</em> <em>ICICI Lombard General Insurance Company Limited, Royal Sundaram Alliance Insurance C

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7

Lemaire, Jean, and G. C. Taylor. "Claims Reserving in Non-Life Insurance." Journal of Risk and Insurance 55, no. 2 (1988): 396. http://dx.doi.org/10.2307/253338.

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8

Buchwalder, Markus, Hans Bühlmann, Michael Merz, and Mario V. Wüthrich. "Valuation portfolio in non-life insurance." Scandinavian Actuarial Journal 2007, no. 2 (2007): 108–25. http://dx.doi.org/10.1080/03461230701251455.

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9

Meyers, Glenn, and G. C. Taylor. "Claim Reserving in Non-Life Insurance." Journal of the American Statistical Association 82, no. 397 (1987): 362. http://dx.doi.org/10.2307/2289204.

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10

Ruohonen, Matti. "Non-Life Insurance Mathematics (Erwin Straub)." SIAM Review 32, no. 1 (1990): 184–85. http://dx.doi.org/10.1137/1032031.

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11

Carroll, Patrick, and G. C. Taylor. "Claims Reserving in Non-Life Insurance." Journal of the Royal Statistical Society. Series A (General) 150, no. 2 (1987): 175. http://dx.doi.org/10.2307/2981647.

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12

Diers, Dorothea, Martin Eling, Christian Kraus, and Marc Linde. "Multi‐year non‐life insurance risk." Journal of Risk Finance 14, no. 4 (2013): 353–77. http://dx.doi.org/10.1108/jrf-04-2013-0036.

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13

Pavić Kramarić, Tomislava, Maja Pervan, and Marijana Ćurak. "Determinants of Croatian Non-Life Insurance Companies’ Efficiency." Croatian operational research review 13, no. 2 (2022): 149–60. http://dx.doi.org/10.17535/crorr.2022.0011.

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Although a relatively large number of studies have been focused on evaluating the efficiency of insurance companies from different aspects, analysis of factors that determine the achieved level of insurers’ efficiency is still in their inception. While these studies primarily encompass insurance companies operating in developed insurance markets, such research based on the sample of Croatian non-life insurers does not exist. Therefore, this paper is focused on the efficiency drivers of the insurance companies that operate in the Croatian non-life insurance market. The research is based on data

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14

Lakstutiene, Ausrine, Rasa Norvaisiene, Jurgita Stankeviciene, and Rytis Krusinskas. "The Impact of Financial Crisis on the Non-Life Insurance Market in Lithuania : Will the Market Growth Expectations be Met?" Olsztyn Economic Journal 10, no. 1 (2015): 5–18. http://dx.doi.org/10.31648/oej.3130.

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The article analyzes the insurance market trends, which have been determined by the financial crisis, and reveals the development features and prospects of non-insurance market, which accounts for almost 70% of the total insurance market, in Lithuania. The obtained results showed that after the market shrank by a quarter in 2009, the insurance sector is recovering, and while the volume of issued insurance premiums increased in 2013, they still remain lower than during the pre-crisis period. 2010 is a distinctive year for the Lithuanian non-insurance market due to a track of unusual abundance o

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15

Asongu, Simplice A. "Technology, Education, Life and Non-life Insurance in Africa." International Journal of Public Administration 43, no. 11 (2019): 915–25. http://dx.doi.org/10.1080/01900692.2019.1660994.

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16

Camino-Mogro, Segundo, and Natalia Bermúdez-Barrezueta. "Determinants of profitability of life and non-life insurance companies: evidence from Ecuador." International Journal of Emerging Markets 14, no. 5 (2019): 831–72. http://dx.doi.org/10.1108/ijoem-07-2018-0371.

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Purpose The purpose of this paper is is to identify the main determinants of insurance profitability on life and non-life segments to obtain which variables affect in each market of the Ecuadorian insurance sector. Design/methodology/approach The authors use a large panel data set with financial information from 2001 to 2017 and estimate the determinants through a panel corrected standard errors regression. Findings The authors found that net premiums, technical reserves, capital ratio and score efficiency are micro-determinants in the life insurance sector, whereas in the non-life sector, the

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17

Hoang Nam, Nguyen Hong, and Ngo Thang Loi. "Development Policy for the Non-Life Insurance Market in Vietnam in the Context of Industry 4.0." International Journal of Management Studies and Social Science Research 07, no. 02 (2025): 313–25. https://doi.org/10.56293/ijmsssr.2025.5537.

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The development of the non-life insurance market is vital for supporting capital market growth and investment, as well as for enhancing economic stability and development. This study assesses the current state of policies for developing the non-life insurance market in Vietnam in the context of Industry 4.0. The research specifically focuses on evaluating these policies across several dimensions: entry policies for the non-life insurance sector, policies for the provision of non-life insurance products, financial policies for non-life insurance companies, policies for supervising non-life insu

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18

Dr., Sachin S. Rudrawar. ""ROLE AND IMPORTANCE OF BANCASSURANCE IN INDIA"." International Journal of Advance and Applied Research 2, no. 17 (2022): 240–44. https://doi.org/10.5281/zenodo.7053592.

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<strong><em>Abstract: </em></strong> <em>In India the concept of Bancassurance appears to be gaining ground rapidly both through commission based arrangements and joint ventures between banks and insurance companies. Banks with their geographical spread and penetration in terms of customer reach of all segments have emerged as viable source of distribution of insurance products8. All most all the new entrants along with LIC and GIC have formed relationships with several banking partners after the formation of the required regulation. </em><em>The study is a based on secondary sources of data a

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19

Tokutsune, Yasuyuki. "Non-life Insurance Company and Rating Information." Hokengakuzasshi (JOURNAL of INSURANCE SCIENCE) 2020, no. 650 (2020): 650_65–650_84. http://dx.doi.org/10.5609/jsis.2020.650_65.

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20

Schlütter, Sebastian. "Optimal taxation in non-life insurance markets." Geneva Risk and Insurance Review 44, no. 1 (2018): 1–26. http://dx.doi.org/10.1057/s10713-018-0035-x.

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21

Cassidy, A. A. "AIDS and the Non-Life Insurance Market." Geneva Papers on Risk and Insurance - Issues and Practice 13, no. 4 (1988): 332–41. http://dx.doi.org/10.1057/gpp.1988.25.

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22

Ramlau-Hansen, Henrik. "A solvency study in non-life insurance." Scandinavian Actuarial Journal 1988, no. 1-3 (1988): 3–34. http://dx.doi.org/10.1080/03461238.1988.10413835.

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23

Ramlau-Hansen, Henrik. "A solvency study in non-life insurance." Scandinavian Actuarial Journal 1988, no. 1-3 (1988): 35–59. http://dx.doi.org/10.1080/03461238.1988.10413836.

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24

Djuric, Zlata. "Collective risk model in non-life insurance." Ekonomski horizonti 15, no. 2 (2013): 163–72. http://dx.doi.org/10.5937/ekonhor1302163d.

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25

Darooneh, A. H. "Non-life insurance pricing: multi-agent model." European Physical Journal B 42, no. 1 (2004): 119–22. http://dx.doi.org/10.1140/epjb/e2004-00363-x.

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26

Ohlsson, Esbjörn, and Jan Lauzeningks. "The one-year non-life insurance risk." Insurance: Mathematics and Economics 45, no. 2 (2009): 203–8. http://dx.doi.org/10.1016/j.insmatheco.2009.06.001.

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27

Bohnert, Alexander, Nadine Gatzert, and Andreas Kolb. "Assessing inflation risk in non-life insurance." Insurance: Mathematics and Economics 66 (January 2016): 86–96. http://dx.doi.org/10.1016/j.insmatheco.2015.11.003.

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28

de, Andrés-Sánchez. "Fuzzy claim reserving in non-life insurance." Computer Science and Information Systems 11, no. 2 (2014): 825–38. http://dx.doi.org/10.2298/csis121225045a.

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This paper develops several expressions to quantify claim provisions to account in financial statements of a non-life insurance company under the hypothesis of a fuzzy environment. Concretely, by applying the expected value of a fuzzy number and the more general concept of value of a fuzzy number to the ANOVA claim predicting model [2] we estimate claim reserves to account in insurer?s balance sheet and income account.

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29

Abidin, Zaenal, and Emilyn Cabanda. "EFFICIENCY OF NON-LIFE INSURANCE IN INDONESIA." Journal of Economics, Business, and Accountancy | Ventura 14, no. 3 (2011): 197. http://dx.doi.org/10.14414/jebav.v14i3.46.

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30

Grize, Yves‐Laurent, Wolfram Fischer, and Christian Lützelschwab. "Machine learning applications in non‐life insurance." Applied Stochastic Models in Business and Industry 36, no. 4 (2020): 545–47. http://dx.doi.org/10.1002/asmb.2564.

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31

Beirlant, Jan, and Jozef L. Teugels. "Modeling large claims in non-life insurance." Insurance: Mathematics and Economics 11, no. 1 (1992): 17–29. http://dx.doi.org/10.1016/0167-6687(92)90085-p.

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32

Mani Upadhyaya, Yadav, Khom Raj Kharel, Narayan Prasad Aryal, and Basu Dev Lamichhane. "Contribution of the non-life insurance sector to the economic growth of Nepal: Analysis from the EGLS approach." Insurance Markets and Companies 15, no. 1 (2024): 30–39. http://dx.doi.org/10.21511/ins.15(1).2024.03.

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Nepal’s non-life insurance sector holds immense potential to drive economic growth and boost the nation towards a secure financial future. Embracing this potential is a goal and a pivotal catalyst for substantial change. The study aims to determine how the non-life insurance sector can drive economic growth in Nepal. The methodology of this study uses quantitative analysis of financial data from 2013 to 2022 from 20 non-life insurance companies in Nepal and econometric modeling to assess the sector’s impact on economic growth. Using Panel EGLS (Estimated Generalized Least Squares) regression a

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33

Tian, Ling, Shi-Jie Jiang, Guochen Pan, and Ning Zhang. "Non-life insurance price dynamics: evidence from the Chinese insurance market." Economic Research-Ekonomska Istraživanja 31, no. 1 (2018): 171–87. http://dx.doi.org/10.1080/1331677x.2018.1424557.

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34

Farahtulnisa Rozainee, Nurulain, and Isaudin Ismail. "Bivariate Dependence Modelling of a Non-Life Insurance Company: Pair-Copula Construction." International Journal of Science and Research (IJSR) 11, no. 2 (2022): 552–55. http://dx.doi.org/10.21275/sr22210092450.

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35

Pakhnenko, O., O. Zhuravka, V. Podhorna, and A. Sukhomlyn. "ANALYSIS OF COMPETITIVE POSITIONS OF INSURANCE COMPANIES IN THE NON-LIFE INSURANCE MARKET IN UKRAINE." Vìsnik Sumsʹkogo deržavnogo unìversitetu, no. 2 (2019): 88–94. http://dx.doi.org/10.21272/1817-9215.2019.2-11.

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The paper explores the practical aspects of forming a competitive environment in the non-life insurance market of Ukraine and analyzes the competitiveness and financial performance of leading insurance companies. Based on the analysis of non-life insurance market concentration indicators, the authors concluded that there is no clear leader in this market, the level of market concentration is negligible. Based on the analysis of non-life insurance market leaders by volume of gross insurance premiums in the whole market and by main types of non-life insurance (CASCO, motor vehicle liability insu

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36

Kiplang’at, Dennis, and Jennifer Njaramba. "Firm Specific Factors and the Profitability of Listed Non-Life Insurance Firms in Kenya." Cradle of Knowledge: African Journal of Educational and Social Science Research (The) 12, no. 2 (2025): 69–77. https://doi.org/10.4314/ajessr.v12i2.3.

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Insurance as a subset of the financial industry plays a critical function in economic growth of countries. The subsector drives economic sustainability through indemnification of the stakeholders covered in various policies. This is through recompense of parties with insurable interest thus insulation against economic losses. The insurance sector’s contribution to Kenya’s GDP is relatively low (2.24 percent in 2021) compared to other major sectors such as agriculture, but it can be considered as a key enabler particularly in minimizing financial losses in various sectors. Non-life insurance ac

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37

Oluwaleye, Taiwo Olarinre, Sunday Stephen Ajemunigbohun, and Kehinde Emmanuel Abiodun. "Underwriting Operations and Financial Performance: Evidence from Non-Life Insurance Firms in Nigeria." Business Economic, Communication, and Social Sciences Journal (BECOSS) 5, no. 3 (2023): 167–76. http://dx.doi.org/10.21512/becossjournal.v5i3.10232.

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This study investigated the relationship between underwriting operations and the performance of non-life insurance firms in Nigeria. Specifically, the study examined the combined metrics of claim ratio, insurance premium, and re-insurance claims on the return on assets using the non-life insurance firms as bases in Nigeria. The study engaged data within the period of 2011-2020 extracted from the financial statements of five selected non-life insurance firms and analysis of data was conducted with a panel regression procedure. The result showed that insurance premium had a positive significant

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38

Severus, Absalom. "Examining the relationship between non-life insurance premiums and economic growth in Namibia." International Journal of Recent Research in Commerce Economics and Management 9, no. 3 (2022): 73–81. https://doi.org/10.5281/zenodo.7032116.

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<strong>Abstract:</strong> The impact of insurance market activity on financial development is gaining academic attention as the insurance sector grows in emerging markets. This research aims to examine the relationship between non-life insurance premiums and economic growth in the Namibian context by providing recommendations to drive increased penetration across the Namibian economy. The study scrutinizes the explanatory factors of non-life insurance demand in Namibia, using quarterly data from Q1:2010 to Q4:2020  and also the Ordinary Least Square Method.  The variables employed w

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39

Wang, S. "Risk loads in life/non-life insurance: a unified approach." Insurance: Mathematics and Economics 17, no. 3 (1996): 236. http://dx.doi.org/10.1016/0167-6687(96)82373-0.

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40

Chun, Heuiju, and Byunghak Leem. "Face/non-face channel fit comparison of life insurance company and non-life insurance company using social network analysis." Journal of the Korean Data and Information Science Society 25, no. 6 (2014): 1207–19. http://dx.doi.org/10.7465/jkdi.2014.25.6.1207.

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41

Quy Duong, Le. "Asset pricing models for Vietnamese non-life insurance companies." Journal of Eastern European and Central Asian Research (JEECAR) 11, no. 5 (2024): 945–55. http://dx.doi.org/10.15549/jeecar.v11i5.1763.

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This paper aims to perform an extensive asset pricing analysis for the Vietnamese non-life insurance industry between 2008 and 2023. We document that well-known asset pricing models, such as the three-factor and five-factor models developed by Fama and French (1993, 2015), are unable to explain adequately the returns of non-life insurance stocks. Therefore, based on the results of Ammar et al. (2018) and He et al. (2021), we built a five-factor asset pricing model adapted to the Vietnamese non-life insurance industry. Empirical evidence shows that this model is better than other models in expl

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42

Birian, Nungo Akwir, Margaret Oloko Prof., and Dennis Juma Okello (PhD) Dr. "Effect of Entrepreneurial Orientation on Performance of non-life insurance in Kenya." International Journal of Management and Economics Invention 11, no. 03 (2025): 3996–4007. https://doi.org/10.5281/zenodo.14992212.

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ABSTRACT : This research aimed to investigate the impact of entrepreneurial orientation on the performance of non-life insurance in Kenya. The research was based on the Schumpeter’s Theory. The study used a survey research design. The study's target population included 35 non-life insurance businesses licensed by the insurance regulatory authority, serving as the unit of analysis. Two senior and six middle management officials from the 35 non-life insurance companies were selected as respondents. The study used a census research survey. The primary data was gathered using self-administer

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43

Ćurak, Marijana, Sandra Pepur, and Dujam Kovač. "Does financial literacy make the difference in non-life insurance demand among European countries?" Ekonomski pregled 71, no. 4 (2020): 359–82. http://dx.doi.org/10.32910/ep.71.4.3.

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While risk aversion and affordability of insurance are considered as the most important determinants of non-life insurance demand, understanding and knowledge of complex non-life insurance products are less researched. Studies on insurance demand conducted at the cross-section level, which include education, usually use it as a proxy for risk aversion and to a limited extent as a measure of financial literacy. Moreover, the general level of education does not accurately reflect the level of understanding of sophisticated insurance instruments. Consequently, the main aim of this research is to

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44

Prof., Osuka Bernard. O., and Ades George Aderigha. "Non-Life Insurance Sector Premiums and Economic Growth: The Nigerian Experience." International Journal of Multidisciplinary Research and Analysis 04, no. 05 (2021): 638–50. https://doi.org/10.47191/ijmra/v4-i5-23.

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The study examined the relationship amid Non-life insurance premiums and economic growth in Nigeria for the period 1981–2017. The study measured fire premium, Accident premiums, Motor vehicle premium, Marine premiums and miscellaneous premiums as proxies for Insurance sector premiums while Real Gross Domestic Products was used as proxy for Economic growth for the said periods under review. In the course of the study, data were obtained from the website of Central Bank Statistical bulletin and annual report of NIA digest. The Phillips Perron type was used to test for unit root. The Autore

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45

Kolapo, Funso Tajudeen (PhD), Taiwo Olarinre Oluwaleye, and Adedeji Viscker Osasona. "Determinants of Insurance Sector Development in Nigeria." Account and Financial Management Journal 07, no. 03 (2022): 2672–85. https://doi.org/10.5281/zenodo.6382819.

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Abstract Insurance market in Nigeria like other developing African countries have remained small, less pervasive, and underdeveloped with evidence from the abysmally low density and penetration rates. These casts doubt on insurance sector development in Nigeria to question whether the issues are related to dynamics in macroeconomics, demographic, and institutional factors affect the sector. The determinants of insurance sector development in Nigeria for the period 1987 to 2020 follows a multiple regression framework through ARDLbounds cointegrationtesting. The Error Correction Model (ECM) resu

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46

Ilyas, Ashiq Mohd, and S. Rajasekaran. "Productivity of the Indian non-life insurance sector." International Journal of Productivity and Performance Management 69, no. 4 (2019): 633–50. http://dx.doi.org/10.1108/ijppm-04-2019-0147.

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Purpose The purpose of this paper is to analyse the performance of the Indian non-life (general) insurance sector in terms of total factor productivity (TFP) over the period 2005–2016. Design/methodology/approach This study utilises Färe‒Primont index (FPI) to access the change in TFP and its components: technical change, technical efficiency and mix and scale efficiency over the observation period. Moreover, it employs the Mann–Whitney U-test to scrutinise the difference between the public and the private insurers in terms of growth in productivity. Findings The results reveal that the insura

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47

Steffensen, Mogens, and Julie Thøgersen. "PERSONAL NON-LIFE INSURANCE DECISIONS AND THE WELFARE LOSS FROM FLAT DEDUCTIBLES." ASTIN Bulletin 49, no. 1 (2019): 85–116. http://dx.doi.org/10.1017/asb.2018.40.

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AbstractWe view the retail non-life insurance decision from the perspective of the insured. We formalize different consumption–insurance problems depending on the flexibility of the insurance contract. For exponential utility and power utility we find the optimal flexible insurance decision or insurance contract. For exponential utility we also find the optimal position in standard contracts that are less flexible and therefore, for certain nonlinear pricing rules, lead to a welfare loss for the individual insuree compared to the optimal flexible insurance decision. For the exponential loss di

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48

Steffensen, Mogens, and Julie ThøGersen. "PERSONAL NON-LIFE INSURANCE DECISIONS AND THE WELFARE LOSS FROM FLAT DEDUCTIBLES." ASTIN Bulletin 49, no. 01 (2019): 85–116. http://dx.doi.org/10.1017/asb.2019.40.

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AbstractWe view the retail non-life insurance decision from the perspective of the insured. We formalize different consumption–insurance problems depending on the flexibility of the insurance contract. For exponential utility and power utility we find the optimal flexible insurance decision or insurance contract. For exponential utility we also find the optimal position in standard contracts that are less flexible and therefore, for certain nonlinear pricing rules, lead to a welfare loss for the individual insuree compared to the optimal flexible insurance decision. For the exponential loss di

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49

Rapi, Kristio, Dominicus Savio Priyarsono, Siti Jahroh, and Toni Bakhtiar. "Life Insurance Purchasing Behavior in Non-High Income Countries: Case Study in Indonesia." Business Review and Case Studies 6, no. 1 (2025): 122. https://doi.org/10.17358/brcs.6.1.122.

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Background: Life insurance demand in Indonesia is still low, despite its positive contributions to the social and financial sectors, and income continues to grow. The increase in literacy and inclusion of insurance also cannot positively affect life insurance demand.Purpose: This study analyzes the effects of economic and demographic factors on life insurance purchasing behavior, including income, interest rates, inflation, education, and life expectancy.Design/methodology/approach: This study uses secondary data with annual frequency from 2002 to 2022 that obtained from Financial Services Aut

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50

KAMESSAN, NADIA IZZATI, ZAINIL HANIM SAIDIN, and ZARINA MD NOR. "FROM AWARENESS TO ACTION: THE JOURNEY OF NON-INSURANCE POLICYHOLDERS IN MALAYSIA." Quantum Journal of Social Sciences and Humanities 5, no. 5 (2024): 128–39. https://doi.org/10.55197/qjssh.v5i5.442.

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The purpose of this study was to investigate the factors influencing the level of life insurance ownership among non-life insurance policyholders. Malaysia faces the challenge of low insurance penetration, with only 40.4% of the population covered by insurance as of 2022, which underscores the need for greater insurance ownership. A sample population of 450 respondents, who were non-life insurance policyholders, was targeted. 398 non-life insurance policyholders (88.4% of the sample) met the inclusion criteria and took part in the study. SPSS Version 27.0 was used to process the survey data. V

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