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The purpose of this paper is to analyse the performance of the Indian non-life (general) insurance sector in terms of efficiency, productivity and returns-to-scale economies. In addition to this, it identifies the determinants of efficiency.

This study employs a two-stage data envelopment analysis (DEA) bootstrap approach to estimate the level and determinants of efficiency. In the first stage, the DEA bootstrap approach is employed to estimate bias-corrected efficiency scores. In the second stage, the truncated bootstrapped regression is used to identify the effect of firm-level characteristics on the efficiency of insurers. Moreover, the bootstrapped Malmquist index is used to examine the productivity growth over the observation period 2005–2016.

The bootstrapped DEA results show that the Indian non-life insurance sector is moderately technical, scale, cost and allocative efficient, and there is a large opportunity for improvement. Moreover, the results reveal that the public insurers are more cost efficient than the private insurers. It is also evident that all the insurers irrespective of size and ownership type are operating under increasing returns to scale. Malmquist index results divulge an improvement in productivity of insurers, which is attributable to the employment of the best available technology. Bootstrapped DEA and bootstrapped Malmquist index results also show that the global financial crisis of 2008 has not severely affected the efficiency and productivity of the Indian non-life insurance sector. The truncated regression results spell that size and reinsurance have a statistically significant negative relationship with efficiency. It also shows a statistically significant positive age–efficiency relationship.

The results hold practical implications for the regulators, policy makers, practitioners and decision makers of the Indian non-life insurance companies.

This study is the first of its kind that comprehensively investigates different types of robust efficiency measures, determinants of efficiency, productivity growth and returns-to-scale economies in the Indian non-life insurance market for an extended time period.

The purpose of this paper is to investigate the efficiency analysis of the Indian general insurance sector using data envelopment analysis (DEA) and subsequently assess the impact (if any) of the global slowdown on the performance of the allied sector.

The paper aims to analyze the operating performance of 12 general insurance companies in India between 2006-2007 and 2009-2010 using DEA based on secondary data collected from Insurance Regulatory and Development Authority Annual Reports.

Findings clearly indicate that the global economic slowdown has severely affected the performance of the private sector companies; while the public sector companies exhibited relatively lesser variation in performance levels.

The methodology employed in the study estimates relative efficiencies without assuming any functional form; as a result the proper comparison of input utilized with the output produced is not possible. Several other tools like Malmquist Index and two-stage procedure have not been used.

The study brings into light the operating characteristics and efficiencies of the Indian general insurance sector during the global slowdown and therefore holds practical value for policy makers and practitioners as well as for the decision makers of the firms employed in the study.

Introduction: Foreign direct investment (FDI) is a deciding factor in the insurance industry’s growth in any nation. Besides, similar socioeconomic conditions, some countries tend to attract more FDI inflows. This chapter focuses on exploring the FDI in the insurance industry in Brazil, Russia, India, China, and South Africa (BRICS).

Purpose: The chapter aims to explore the current situation of FDI in the insurance industry in BRICS member nations and uncover the factors that have led to higher foreign investments in some countries.

Methodology: Using descriptive and comparative approaches, this chapter explains the FDI scenario in the insurance sector of BRICS nations.

Findings: Based on a comparative analysis, the authors observed that deregulation, increased foreign engagement, and adoption of innovative technology and distribution methods are some avenues that could be worked upon to improve FDIs in the Indian insurance sector.

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.

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.

The results reveal that the insurance sector possesses a very low level of TFP. Also, the results divulge an improvement of 11.98 per cent in TFP of the insurance sector at an annual average rate of 12.41 per cent over the observation period. The growth in productivity is mainly attributable to the improvement of 10.81 per cent in the scale‒mix efficiency. The progress in scale‒mix efficiency is mainly the result of improvements in residual scale and residual mix efficiency. The results also show that the privately owned insurers have experienced a high productivity growth rate than the state-owned insurers.

The results hold practical implications for the regulators, policymakers and decision makers of the Indian non-life insurance companies.

This study is the first of its kind to use FPI, which satisfies all economically relevant axioms and tests defined by the index number theory to comprehensively access the change in TFP of the Indian non-life insurance sector.

Background: Insurance was discovered many centuries before Christ (BC). In the second and third millennia BC, Chinese and Babylonian traders traded risks. Insurance is now the backbone of the economy, but penetration is low in developing countries. Big data, internet of things (IoT), and InsurTech have recently ushered in the fourth industrial revolution in insurance.

Objective: This study examines the Indian challenges and solutions of using Big Data Analytics (BDA).

methodology: A SLR was used to extract themes/variables related to challenges and solutions in adopting BDA in the Indian insurance sector. Google Scholar was searched for relevant literature using keywords. Inclusion and exclusion criteria were used to filter the studies.

Findings: This study identified several barriers to BDA adoption in the Indian insurance industry. Policymakers could use the suggestions to improve insurance service delivery.

Practical implication: Insurers can understand the challenges, and accordingly, they can adopt the proposed solution in this study to enhance the insurance penetration in India.

Introduction: The Indian insurance sector has a large number of insurance companies. More than 20 companies are in the life insurance business, and nearly 35 are non-life insurers – only one public sector company among the life insurers (Life Insurance Corporation (LIC)). However, there are six public sector insurers in the property insurance division. The government policies have recently increased the foreign direct investment (FDI) share from 49% to 74%.

Purpose: The purpose of the study is based on the latest decision by the Government of India (GOI) to increase the FDI in the insurance sector, which was earlier 49% and now increased to 74%. The study will have objectives that impact change in FDI and its effect on customers’ decisions.

Methodology: This chapter is based on secondary information collected from the Insurance Regulatory and Development Authority and Articles from various journals for objectives 1 and 2. Qualitative analysis is done with the use of NVIVO software. There are primary two objectives taken under consideration in this chapter: objective 1: regulatory framework of insurance sector post-FDI change in limits by GOI and objective 2: customer awareness regarding changed limits of FDI in the insurance sector and its various factors. Fifty-four interviews were conducted, out of which a total of 40 responses have been considered for final analysis. An incomplete and unclear answer has been excluded from the study.

Findings: In the study’s findings, it was found that in accordance with the first objective, GOI changes policies according to time to time. Foreign Direct Investment (FDI) in the insurance sector recently increased by GOI Earlier, it increased in the year 2015 and recently this year, it increased by 49% again to 74%. In the second objective findings, the awareness about changes in FDI in the insurance sector respondent’s sentiments is positive and constructive. A maximum of respondents has said that they are aware of the insurance sector and the participation of various foreign international players in the insurance industry.

The purpose of this article is to evaluate revenue efficiency performance of life insurance companies in India. The study also compares if private or public insurance sector is more “revenue efficient”. Furthermore, the study determines the nature of return to scale (RTS) and identifies the leaders and laggards amongst insurance companies operating in India.

Revenue efficiency is calculated by employing data envelopment analysis – a non-parametric approach, on a data set of 24 insurance companies over the period 2013–2014 to 2017–2018.

The empirical results suggest that life insurance companies in India could generate only 34.4% of revenue, which is very less than what these are expected to generate from the same inputs. Majority of life insurance companies operating in India are operating at decreasing return to scale (DRS). There is a reduction in leaders and the highest proportion of companies is falling in the category of laggards.

As per the best knowledge of researchers, no empirical work has been carried out with respect to measuring the revenue efficiency of Indian insurance companies. The current study appropriately fills the gap by not only calculating the revenue efficiency scores of insurance companies in India but also provides insights into the causes of revenue inefficiencies. It also gives implications for efficient and effective management of insurance companies.

The role of financial institutions and financial intermediaries in fostering the economic growth by improving the efficiency of capital accumulation, encouraging savings and ultimately improving the productivity of the economy has been well accepted by now. Recent studies show that the insurance industry can improve the economic growth through financial intermediation, risk aversion and generating employment. This study aims to find the relationship between life insurance industry and economic development in India.

The study uses the VAR‐VECM model to find out the long run and short run relationship (if any) between life insurance growth and economic growth along with Granger causality test to suggest any causal relationship.

This study finds that there is long term relationship between life insurance industry and economic development in India. And the Granger causality test suggests that life insurance sector improves the overall economic development in India and the reverse is not significant.

The only limitation to study the relationship between life insurance sector development and economic development is the data set which has been used is annual data as the quarterly data were not available for insurance industry.

The study documented the long run relationship between life insurance industry and economic development in India and finds that the life insurance sector improves the overall economic development in India. This would help us to understand the implications of the life insurance market development in the post reform era.

There is a dearth of literature on the Indian economy in relation to the insurance sector, specifically the life insurance sector. This is the first attempt to study the impact of life insurance development on Indian economy after the reforms initiated in the insurance sector.

International business/International marketing.

Courses: the case is directly related to courses on “International Business” and “International Marketing” in the Master of Business Administration programme.

Training programmes: management development programmes for working executives, on the topics “Business across borders”, “Business stabilization in foreign markets”.

In 1999, the liberalization of the insurance sector as per the recommendations of the Malhotra committee gave way for privatization and foreign firms entered this sector through joint ventures. The business growth, which was enjoyed by these firms from 1999 to 2008, was tremendous. The growth percentage started declining following the global economic downturn in the capital markets. This situation compelled the insurance firms to re-look into their business strategy. On one hand whatever growth they had, 80 percent of it was through unit linked insurance plans depending on the capital market. On the other, it was identified that in a country like India the untapped market potential was among the rural millions. Reaching those people who are at the bottom of the pyramid necessitated a completely new business model to be developed as the need of the hour. The take stock of the position at this vnjuncture is the crux of the present case study, which envisages finding out alternative delivery models to suit the Indian rural market taking into account the intrinsic nature of life insurance and the basic living styles and mentality of the rural folk.

After discussion and analysis of this case, students will be able to:

• understand how market culture in a target country differs from that in the home country;

• appreciate how challenges in a developing country market have their own unique features to be understood;

• identify various courses of action and evaluate them on the basis of the host country factors;

• understand the “international planning process”; and

• appreciate how important it is for a country manager of a multinational firm to plan and execute the marketing mix suited to the inherent qualities of the target market.

understand how market culture in a target country differs from that in the home country;

appreciate how challenges in a developing country market have their own unique features to be understood;

identify various courses of action and evaluate them on the basis of the host country factors;

understand the “international planning process”; and

appreciate how important it is for a country manager of a multinational firm to plan and execute the marketing mix suited to the inherent qualities of the target market.

Teaching notes.

This paper aims to measure the change and the sources of change in total factor productivity (TFP) of the Indian non-life insurance sector over the period 2005–2016.

This study employs the bootstrapped Malmquist index (MI) to assess the changes in the TFP and adopts a decomposition approach proposed by Balk and Zofío (2018). Moreover, it utilises truncated regression to identify the determinants of the TFP. In addition, it employs Wilcoxon-W test and t-test to scrutinise the difference between the state-owned and the private insurers in terms of variations in TFP and its various components.

The results divulge a miniature improvement in TFP of the insurance sector, which is primarily attributable to the improvement in scale efficiency (economies of scale). The results also reveal that there are no significant TFP differences across the ownership. However, private insurers have better scale efficiency and lower input-mix efficiency than state-owned insurers. In addition, the results unveil that size, diversification and reinsurance have a negative impact on the TFP, while age has a positive impact on it.

The results may help the policymakers to frame new consolidation policies. Moreover, the findings may guide the decision-makers of the Indian non-life insurance companies to abate inefficiency and improve TFP.

This study estimates bias-corrected changes in TFP and efficiency in the non-life insurance sector. Moreover, it adopts an elaborated decomposition of the MI to identify the true sources of change in the TFP.