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Purpose: In addition to the liberalisation policy, big data has revolutionised the level of awareness among customers about the quality and prices of insurance products. The rationale behind this study is to underline the issues in managing product portfolios in a disruptive environment, where a sudden and unexpected situation like COVID-19 pandemic is going to challenge the traditional models and insurance covers of organisations as well as individuals.

Methodology: The study is based on secondary data. The scope of the study will only be confined to the top two general insurance companies in India based on year of registration and market share to compare their product portfolios during pre- and post-liberalisation periods ranging from 1985–1986 to 2000–2001 and 2001–2002 to 2018–2019, respectively.

Findings: There is a lack of a balanced product portfolio for fulfilling the varying needs of customers. The insurance companies needed to set up different portfolios and should provide separate covers for natural catastrophes such as floods, earthquakes, landslides, tsunami, and the occurrence of new pandemics like COVID-19.

Significance: The study highlights that the outbreak of COVID-19 and similar pandemics or global emergencies need special preparation from the insurance sector.

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.

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.

According to Global Healthcare Security Index 2021, India ranked 66 out of 195 countries, indicating the need and scope for improvement. The Cooperative healthcare system which has been rendering exemplary services is yet to gain visible recognition in India. Given the need for upgrading the health infrastructure in India and providing more affordable health services to the country’s growing population, it would help appreciate the large role that cooperative healthcare can play along with others. This study explores the structure, conduct, and performance of healthcare co-operatives in India, the factors contributing to their success and failure, and the challenges they face. The Health Cooperatives have a strong presence in Kerala and Karnataka and are also coming up in other parts of the country. However, a detailed database of them for public awareness is very limited. The cooperative hospitals can meet the basic requirements of curative treatment in rural and poorly-endowed urban areas. The democratic way in which they function makes them a destination for a financially weaker section. They must retain this feature. The study covers two successful cases which reveal that India needs a more dense healthcare cooperative network. Since cooperative hospitals in tune with the spirit of service run on the principle of being ‘Not-for-Profit’ they need to be supported by the governments more liberally, without however interfering with their governance and administration.

Introduction: Big data in the insurance industry can be defined as structured or unstructured data that can affect the rating, marketing, pricing, or underwriting. The five Vs of big data provide insurers with a valuable framework for converting their raw data into actionable information. These five Vs are specifically: (1) Volume: The need to look at the type of data and the internal systems; (2) Velocity: The speed at which big data is generated, collected, and refreshed; (3) Variety: Refers to both the structured and unstructured data; (4) Veracity: Refers to trustworthiness and confidence in data; and (5) Value: Refers to whether the data collected are good or bad.

Purpose: Insurance companies face many data challenges. However, the administration of big data has allowed insurers to acknowledge the demand of their customers and develop more personalised products. In addition, it can be used to make correct decisions about insurance operations such as risk selection and pricing.

Methodology: We do this by conducting a systematic literature review on big data. Our emphasis is on gathering information on the five Vs of the big data and the insurance market. Specifically, how big data can help in data-driven decisions.

Findings: Big data technology has created an endless series of opportunities, which have ensured a surge in its usage. It has helped businesses make the process more systematic, cost-effective, and helped in the reduction in fraud and risk prediction.

Healthcare is indispensable for any civilisation to attain a good quality of life and well-being on both mental and physical levels. The healthcare domain primarily falls under pharma, medical, biotechnology, and nursing. Also, other fields may be aligned with these primary fields. Healthcare amasses the contemporary trends and knowledge of upcoming techniques to improve healthcare processes. The practitioners are primarily doctors, nurses, specialists and health professionals, hospital administrators, and health insurance.

It is a fundamental attribute needed for any society to attain good quality of life and well-being in mental and physical health. It is a fundamental right of people to receive good healthcare where drug treatment and hospitalization are available at a nominal cost, as a requirement of today’s modern era. There appears to be a significant disparity in the availability of good healthcare in rural areas compared to urban in India. Even though we enter the digital era with the facilities offered in Industry 4.0 and other advanced technologies brings about a significant change of overall processing within healthcare systems. During the pandemic of COVID-19, there has been digital transformation with success globally. Healthcare cooperatives are a new norm to support the healthcare systems globally. The chapter discusses Gampaha healthcare cooperative and reviews Ayushman Sahakar scheme in India. The reforms require time to evolve.

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.

The study explores the impact of the general insurance industry’s financial soundness on Sri Lanka’s financial performance by using the CARAMELS approach for seven years (2011–2019) and using secondary data. The study utilised panel data regression analysis. Return on Asset was used as the proxy of financial performance while the 10 dimensions were employed. The best-fitted model is the fixed effect model (FEM), which indicates capital adequacy ratio (CAR) and profitability ratio has a positive impact and that the retention ratio (RR), claims ratio, and expenses ratio harm financial performance in the general insurance sector. The study concluded that capital adequacy, earnings and profitability, reinsurance, and actuaries are important predictors of financial performance for general insurers. The findings help the regulator and general insurers set better performance targets and enable insurance company managers to allocate capital more efficiently.

Introduction: The Internet has tremendously transformed the computer and networking world. Information reaches our fingertips and adds data to our repository within a second. Big data was initially defined as three Vs, where data come with greater variety, increasing volumes and extra velocity. Big data is a collection of structured, unstructured and semi-structured data gathered from different sources and applications. It has become the most powerful buzzword in almost all the business sectors. The real success of any industry can be counted based on how the big data is analysed, potential knowledge is discovered and productive business decisions are made. New technologies such as artificial intelligence and machine learning have added more efficiency to storing and analysing data. This big data analytics (BDA) becomes more valuable to those companies, focusing on getting insight into customer behaviour, trends and patterns. This popularity of big data has inspired insurance companies to utilise big data at their core systems and advance the financial operations, improve customer service, construct a personalised environment and take all possible measures to increase revenue and profits.

Purpose: This study aims to recognise what big data stands for in the insurance sector and how the application of BDA has opened the door for new and innovative changes in the insurance industry.

Methodology: This study describes the field of BDA in the insurance sector, discusses the benefits, outlines tools, architectural framework, the method, describes applications in general and specific and briefly discusses the opportunities and challenges.

Findings: The study concludes that BDA in insurance is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs. Its potential is great; however, there remain challenges to overcome.