Life Insurance Sector Research Articles

Beyond Automation: A Rigorous Testing Framework for Reliable AI Chatbots in Life Insurance

AI-driven chatbots are transforming customer service in Life Insurance, offering policyholders instant support, streamlined inquiries, and personalized recommendations. However, deploying these chatbots effectively requires addressing unique challenges, including interpreting complex insurance terminology, ensuring regulatory compliance, and maintaining data security and user privacy. This research introduces a detailed testing framework specifically tailored to Life Insurance chatbots, covering functional, non-functional, AI-specific, and compliance testing to guarantee accuracy, reliability, and adherence to legal standards. The framework emphasizes essential practices for verifying natural language understanding, sensitive data handling, and empathetic responses for users navigating critical life events. This research highlights the critical role of targeted testing to deliver robust, user-centered chatbot solutions in the Life Insurance sector.

THE INSURANCE MARKET IN ROMANIA – MOTOR THRID PARTY LIABILITY INSURANCE: COMMUNICATION ON DEVELOPMENTS, RISKS, CHALLENGES AND PERSPECTIVES

The risks faced by the Romanian insurance market are significant and come from both the difficult global context and the internal dynamics. Paradoxically, however, the underdevelopment of the market, especially in the life insurance sector, and the dependence on the mandatory insurance type RCA, reduce the exposure of Romanian insurance companies to some risks, such as a fall in income or an increase in interest rates. In this context, the paper aims to make an estimate of the risks and challenges in the RCA insurance market for the coming years starting from a series of official data for these mandatory policies from 2019-2023. We find that compulsory car insurance stands out as a bright spot, comprising over 45% of total premiums. A small number of companies dominate the market, with the top 10 controlling roughly 60%. In the compulsory car insurance sector, there's a mix of growth and decline: voluntary premiums are rising, but the number of contracts is falling. Despite fewer claims, the average cost per claim has increased compared to the previous year. Overall, the results suggest that the dependence on mandatory insurance like RCA paradoxically shields Romanian insurance companies from certain risks.

Accelerating Time-to-Market in Life Insurance: The Power of AI-Driven Test Automation Frameworks

The Life Insurance sector grapples with distinct challenges, balancing multifaceted operational workflows, rigorous compliance standards, and the surging demand for swift software deployment. Conventional Quality Assurance (QA) paradigms often fall short in delivering the responsiveness required by today's digital transformation efforts. This paper examines how Artificial Intelligence (AI)-enhanced test automation frameworks can substantially truncate time-to-market while ensuring software excellence. By leveraging advanced predictive analytics, strategic test case prioritization, and integrated Continuous Integration/Continuous Delivery (CI/CD) processes, Life Insurance enterprises can accelerate software launch cycles with improved dependability, thereby meeting the ever-evolving expectations of the marketplace and regulatory entities.

Enterprise Risk Management and Performance of Insurance Companies

Purpose: This research aims to investigate the impact of risk identification (RI), risk assessment (RA), risk mitigation (RM), and risk management (RMG) on institutional performance (IP). The objective is to analyze both individual and combined effects of these risk management practices on institutional outcomes.Methods: The study used descriptive and causal research design. The data were collected using structured questionnaire with five-point likert scale, targeting 151 managers, officers, and department heads from both life and non-life insurance sectors from Rupendehi district. The correlation analysis was used to examine the relationships between variables and Stepwise regression analysis to explore the effect.Results: It reveals that RA, RM and RMG had significant positive effect on institutional performance at individual level. When they are analyzed in single model RA and RM were only found significant. RI, while consistently positive, was found to be statistically insignificant across all models. RA and RM are significant variables of institutional performance, while RI and RMG play lesser roles.Conclusion: it is necessary to acquire deeper understanding on how risk management practices enhance institutional outcomes.

The Development of the Life Insurance Market in Central and Eastern European Countries

Motivation: The need to implement the process of economic transformation in the recent past is what significantly differentiates the countries of Central and Eastern Europe from other members of the European Union. Integration into the financial system of the European Union has been an important factor influencing the process of transformation of the life insurance sector and the establishment of the level of competition, as well as the quality and scope of insurance services offered. In addition, the improvement in the macroeconomic situation and the increase in household income have had a significant impact on the growth in demand for insurance products from the life insurance segment. Despite positive changes, the insurance market of Central and Eastern European countries remains a relatively underdeveloped market, and its structure, unlike that of Western European countries, is dominated by property insurance. This points towards a need for further research into the determinants of life insurance market growth in this region of Europe. Aim: The aim of this paper is twofold. The first part presents an assessment of the level of development of the life insurance market in ten countries of Central and Eastern Europe over the period 2011-2021 using the method of multivariate comparative analysis in dynamic terms. The second part of the paper is devoted to an attempt to identify the determinants of the development of this market using econometric models for panel data. Results: The life insurance market varies widely among the group of countries considered. The trends of change during the period under consideration were also different. The most severe downturn in the life insurance market was recorded in Poland and the Czech Republic. Significant development was observed in Lithuania and Latvia, countries with an underdeveloped market in the past. The econometric models used confirmed the impact of economic development on the life insurance market.

A Study on Public Sector and Private Sector Insurance in India

India’s insurance sector has been growing rapidly in the last decade. Different reforms have been implemented to stoke for the sector’s growth. But still has a long way to go, as its share in the global insurance market remains very low. It provides a link between the present and the future. Today India is one of the fastest growing economies of the world. According to the World GDP Ranking 2024 list, India is the fifth largest economy in the world. India is also fifth largest life insurance market in the world’s emerging insurance markets growing at a rate of 32-34% each year. Over the past nine years, the insurance sector has attracted substantial foreign direct investment amounting to nearly US$6.5 billion (Rs.54,000 crore), driven by the government’s progressive relaxation of overseas capita flow regulations. Insurance Industry is a growth-oriented industry. The life insurance sector in India has seen an array of changes in the past one decade. The economic scenario which emerged after globalization, privatization and liberalization has thrown a new challenge before the insurers. The present study is basically discussed regarding growth of private sector and public sector insurance of India, market share of public sector and private sector insurance and overall position of India’s public sector and private sector insurance.

IMPACT OF SERVICE QUALITY ON CUSTOMER LOYALTY IN LIFE INSURANCE SECTOR: THE MEDIATING EFFECT OF CUSTOMER TRUST

The aims of this article is to analyze the Impact Of Service Quality On Customer Loyalty In Life Insurance Sector with The Mediating Effect Of Customer Trust. The primary data has been collected through structure questionnaire by using google form. A descriptive research design is used and the result of this study is based on 72 respondents collected through purposive sampling technique. Statistical tools such as descriptive statistic, one-way ANOVA, independent t-test, correlation analysis, and regression is used to measure the relationship between the variables. The result of this study shows that service quality and customer trust both has an significant relationship with customer loyalty. The study found that trust had a greater influence on determining customer loyalty than service quality. Also there is no any significant effect of demographic factors on customer loyalty. The findings of this article suggest, the insurance company have to increase the quality of service to make a loyal customer and improve the customer trust by providing various scheme and premium. Keywords: Service Quality, Customer Trust, Customer Loyalty, Life Insurance Sector

Risk-Based Premiums of Insurance Guarantee Schemes: A Machine-Learning Approach

Introduction/Main Objectives: This study explores the application of machine-learning techniques to risk-based premium calculations for insurance guarantee schemes within the Indonesian insurance market. This study aims to develop a risk-based premium calculation model using machine-learning techniques in the Indonesian context. Background Problems: A gap exists in determining risk-based premiums for both the life and non-life insurance sectors within the Indonesian insurance market. Identifying and understanding the key variables that significantly influence risk-based capital (RBC) is important, and this research addresses this need. Novelty: This paper is the first to apply machine learning to calculate risk-based premiums in the context of the Indonesian insurance market. The distinction between the life and non-life insurance sectors in terms of the importance of its variables and itsselection of an optimal model further enrich its unique approach. Research Methods: We employed gradient-boosted and decision-tree models to identify key factors impacting risk-based capital. Furthermore, we leveraged clustering techniques to categorize companies into distinct risk tiers, aiming to enable more precise risk-based premium rate calculations. Finding/Results: The findings reveal significant differences between the life and non-life insurance sectors in terms of key variables that impact their risk-based capital. These insights lead to the categorization of insurance companies into distinct risk tiers whichhelps to more accurately calculate risk-based premiums. Conclusion: Machine learning can serve as a powerful tool in refining insurance risk management practices, ultimately benefiting insurers, policyholders, and regulators alike.

Factors Influencing Underwriting Performance of the Life and Non-Life Insurance Markets in South Africa: Exploring for Complementarities, Nonlinearities, and Thresholds

ABSTRACT Underwriting is crucial for insurers’ performance and sustainability, yet empirical evidence on factors influencing its performance has received limited attention. Therefore, this study investigates this phenomenon considering South Africa’s life and non-life insurance sectors between 2013–2019. Using the generalized method of moments and the bootstrap quantile regression techniques for analysis, the findings show that insurance size, market share, and investment income significantly and positively impact underwriting performance. However, premium growth weakens the underwriting performance of both sectors. Also, non-life insurance shows a positive relationship for reinsurance, while life insurers present an inverse relationship. Underwriting risk negatively impacts non-life performance across quantiles, while life insurer risk was negative in higher quantiles. More so, initial solvency levels weaken underwriting performance, while extreme increase improves it, implying a direct U-shaped relationship. Hence, highly solvent insurers are more likely to succeed in underwriting operations. Additionally, market share complements return on assets in promoting underwriting performance. Policy recommendations are discussed.

Analysis of IDBI Federal Life Insurance's Financial Performance and Statements in NCR: An In-Depth Review

The research paper delves into the financial statement analysis of IDBI Federal Life Insurance, aiming to conduct a thorough examination of its financial standing. It will encompass an extensive review of the company's financial statements, key ratios, capital structure, profitability, liquidity, and solvency. Moreover, the study will compare the company's financial performance with that of its peers in the life insurance sector to pinpoint strengths and weaknesses. Recommendations for improvement will be proposed based on these findings. Additionally, the research will evaluate the influence of external factors like economic conditions, regulatory changes, and market trends on the company's financial performance. The methodology involves collecting and analyzing financial data, performing ratio analysis, and drawing conclusions to provide actionable insights. Ultimately, the research aims to offer valuable insights into IDBI Federal Life Insurance's financial health and performance, guiding strategies for sustainable growth and success.

In-Depth Financial Statement Review of IDBI Federal Life Insurance in New Delhi: A Comprehensive Analysis

The research paper delves into the financial statement analysis of IDBI Federal Life Insurance, aiming to conduct a thorough examination of its financial standing. It will encompass an extensive review of the company's financial statements, key ratios, capital structure, profitability, liquidity, and solvency. Moreover, the study will compare the company's financial performance with that of its peers in the life insurance sector to pinpoint strengths and weaknesses. Recommendations for improvement will be proposed based on these findings. Additionally, the research will evaluate the influence of external factors like economic conditions, regulatory changes, and market trends on the company's financial performance. The methodology involves collecting and analyzing financial data, performing ratio analysis, and drawing conclusions to provide actionable insights. Ultimately, the research aims to offer valuable insights into IDBI Federal Life Insurance's financial health and performance, guiding strategies for sustainable growth and success.

Sustainability and Practices of Insurance Companies: Literature Review

Abstract: The objective of this paper is to review the literature on the relationship between insurance companies practices and sustainable development, focusing on the Environmental, Social, and Governance (ESG) approach discussed in both developed and developing countries. Insurance companies encounter numerous opportunities and threats related to sustainability, with climate change and environmental pollution standing out as the most significant challenges impacting the insurance industry, particularly the life insurance sector. The paper concludes that insurance companies are prepared to offer sustainable insurance products in the future by committing to environmental and social standards. However, challenges exist regarding adherence to governance principles, particularly due to the predominance of small and medium-sized insurance companies. The current study also underscores the intimate connection between the insurance industry and sustainability factors. They mutually influence each other in an integrative relationship, necessitating the integration of ESG factors into the business strategies of insurance companies.

The Development of Forecasting Models for Life Insurance Data by Employing Time-series Analysis and Machine Learning Technique

This article is conducted with the primary objective of investigating and comparing various forecasting models, aiming to identify the optimal model for life insurance data. For this investigation, we have employed a comprehensive dataset containing monthly direct premium data from the Thai life insurance sector, spanning from January 2003 to December 2022. Our approach involves the development of time-series models to forecast direct premiums, initially employing the SARIMAX framework. Subsequently, we have introduced an additional time-series forecasting model that incorporates SVR, collectively referred to as the SVR-SARIMAX model. The evaluation criteria used for model comparison encompass the Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), and the Coefficient of Determination (R2). The results of our analysis demonstrate that the SARIMAX model outperforms both the SVR and SVR-SARIMAX models, primarily due to the linear pattern in the relationship between the independent and dependent variables. Nevertheless, it is noteworthy that the proposed SVR-SARIMAX model exhibits an improvement in prediction accuracy compared to the standalone non-linear model (SVR), even though the linear model (SARIMAX) still demonstrates superior accuracy.

Aggregate lapsation risk

We study aggregate lapsation risk in the life insurance sector. We construct two lapsation risk factors that explain a large fraction of the common variation in lapse rates of the 30 largest life insurance companies. The first is a cyclical factor that is positively correlated with credit spreads and unemployment, while the second factor is a trend factor that correlates with the level of interest rates. Using a novel policy-level database from a large life insurer, we examine the heterogeneity in risk factor exposures based on policy and policyholder characteristics. Young policyholders with higher health risk in low-income areas are more likely to lapse their policies during economic downturns. We explore the implications for hedging and valuation of life insurance contracts. Ignoring aggregate lapsation risk results in mispricing of life insurance policies. The calibrated model points to overpricing on average. In the cross-section, young, low-income, and high-health risk households face higher effective mark-ups than the old, high-income, and healthy.

Scale elasticity and technical efficiency measures in two-stage network production processes: an application to the insurance sector

In performance analysis with tools such as data envelopment analysis, calculations of scale properties of the frontier points are studied using both qualitative and quantitative approaches. When the production process is a bit complicated, the calculation needs to be modified. Most existing studies are focused on a single-stage production process under the constant or variable returns to scale specification. However, some processes have two-stage structures, and, in such processes, the concepts of scale elasticity and returns to scale are inextricably related to the conditions of the stages of production. Thus, an evaluation of efficiency, scale elasticity, and returns to scale is sensitive to stages. In this study, we introduced a procedure to calculate technical efficiency and scale elasticity in a two-stage parallel-series production system. Then, our proposed technical efficiency and scale elasticity programs are applied to real data on 20 insurance companies in Iran. After applying our estimations to a real-world insurance industry, we found that, (i) overall, the total inputs of insurers in the life insurance sector should be reduced by 9%. Moreover, the inputs of nonlife insurers should be reduced by 50%. The final output in the investment sector must be increased by 48%. (ii) There are inefficiencies among all insurers in the investment sector, and to improve technical efficiency, the income from investments should be increased significantly. (iii) Finally, the efficiency and elasticity characterizations of insurers are directly subject to stages.

The Role of Value Co-Creation Towards Non-financial Performances: Mediating Effect of Customer Support Ticket in the Context of Life Insurance Sector in Sri Lanka

Nowadays, value co-creation plays a vital role in acquiring new business and retaining customers in the competitive business world. Understanding customers and providing them with personalized experiences has become a trend. Value co-creation also plays a crucial role in brand development, as it contributes to brand equity, reputation, and credibility. These factors guide consumer decisions, determining whether they become loyal to a brand or switch to another. Despite its importance, the specific mechanisms through which value co-creation impacts non-financial performances in the life insurance sector in Sri Lanka have not been thoroughly explored. Therefore, the main purpose of this research is to study the impact of value co-creation on the non-financial performances of life insurance policies in Sri Lanka. Dimensions of value co-creation, such as relational orientation, customer involvement, freedom of co-creation, and degree of collaboration, will be examined, along with the mediating effect of customer support tickets. A quantitative research strategy will be employed, utilizing data collected through surveys. The researcher has developed a scale based on previous literature to measure value co-creation and non-financial performances. Reliability and validity of the scales were tested using survey data. The study was conducted in a descriptive manner, allowing for natural settings and avoiding researcher interference. Primary data were collected from a convenient sample of 142 employees working in life top performing insurance companies residing in the Western Province. Regression and multiple regression analyses were conducted to examine the relationships. The results revealed that all elements of value co-creation significantly impact the non-financial performances of life insurance policies, and the moderator and mediator effects supported the framework. Finally, the researcher presented several recommendations for marketing strategies based on the study's results. This research contributes to the existing literature and fills the practice gap, providing avenues for future researchers to explore potential areas. Overall, this study emphasizes the importance of value co-creation in the life insurance sector, highlights its impact on non-financial performances, and offers valuable insights for marketing strategies in Sri Lanka.

The Influence of Job Security and Psychological Contract Fulfilment on Organisational Citizenship Behaviour in Indian Private Life Insurance Sector

The goal of the article is to empirically link the employment security to the employee’s organisational citizenship behaviour (OCB) with examining the impact of psychological contract fulfilment (PCF). The discretionary behaviour of the employees towards the organisation and towards other employees of the organisation is very crucial as this is the element which affects the productivity of the employees in the organisation and how much an employee is attached to his organisation is related to his OCB which he exhibits. This study proposes to interpret and examine the associations between psychological contract and OCB and job security (JS) in the Indian Life Insurance sector so as to raise the light for the managers in Life Insurance sector to improve JS, providing a better experience in terms of psychological contract which will improve their citizenship behaviour. The Life Insurance companies are at a struggle point of retaining their talented manpower as this sector is the budding sector of India which is growing at a rate of 32% annually. For this, promising the JS is the tool in their hand which will directly impact their OCB also and hence their performance will also boost up. Data was collected from 288 full time employees of private life insurance companies and then structural equation modelling was applied to study the relationship. The results demonstrate the positive and significant relationship of JS and PCF on the OCB in the private life insurance sector.

Economic uncertainty and life insurance: Bayesian Network Analysis at the level of European Union

This paper examines the relationship between economic uncertainty and the life insurance sector in the member states of the European Union (EU), with a focus on several key macroeconomic indicators, such as inflation, Gross Domestic Product growth and unemployment. Using a comprehensive dataset covering the diversity of the EU Member States over a ten-year period, econometric methods, like Bayesian Network Analysis are used to analyse the relationship between economic uncertainty indicators and life insurance performance indicators. The findings suggest a complex interplay between economic indicators and life insurance. Inflation appears as a significant factor, and unemployment, another crucial economic indicator, shows a mixed relationship in terms of life insurance demand. Therefore, in the context of an interconnected global economy, understanding how economic uncertainty influences demand for life insurance products is essential for policymakers, insurers and consumers alike.

A Comprehensive Study on Life Insurance at ICICI Prudential Life Insurance: Insights into Customer Perceptions and Industry Dynamics

This research endeavors to conduct an in-depth examination of life insurance offerings at ICICI Prudential Life Insurance, a prominent player in the insurance industry. With life insurance being a critical component of financial planning, this study aims to explore customer perceptions, satisfaction levels, and industry dynamics to provide a comprehensive understanding of ICICI Prudential's position in the market. Utilizing a mixed-methods approach, this research combines qualitative insights gathered through customer interviews and focus group discussions with quantitative surveys to analyze and compare various aspects of life insurance offerings at ICICI Prudential. The qualitative aspect seeks to uncover nuanced perspectives on customer experiences, while quantitative analysis aims to identify trends, correlations, and statistical significance. The study will explore the range of life insurance products offered by ICICI Prudential, including term insurance, endowment plans, and unit-linked insurance plans (ULIPs). It will assess customer satisfaction levels regarding policy features, premium affordability, claim settlement processes, and overall service quality. Furthermore, the research will investigate industry dynamics, including market trends, regulatory influences, and competitive positioning, to provide a holistic view of ICICI Prudential Life Insurance within the broader insurance landscape. The findings from this research are expected to offer valuable insights for insurance professionals, policymakers, and customers alike. By understanding customer perceptions and industry dynamics, ICICI Prudential can refine its strategies, enhance customer satisfaction, and contribute to the ongoing development of the life insurance sector. This study serves as a foundation for informed decision-making and future research within the realm of life insurance at ICICI Prudential Life Insurance.

Unveiling productivity growth in Indian life insurance firms through data envelopment analysis

This study aims to examine total factor productivity (TFP) growth in the Indian life insurance sector from 2008?09 to 2017?18 using a non-parametric frontier methodology. The methodology's unique approach over a decade and nine observation windows provides insights into industry dynamics. Results indicate a negligible role of efficiency change, emphasizing the industry's reliance on technical advancements. The results are pivotal for industry stakeholders, policymakers, and researchers aiming to boost efficiency and competitiveness. The findings underscore the need for strategic adaptation to technological shifts and optimized managerial practices to drive sustainable productivity growth in the dynamic landscape of the Indian life insurance sector.