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Financial assurance rules, also known as financial responsibility or bonding requirements, foster cost internalization by requiring potential polluters to demonstrate the financial resources necessary to compensate for environmental damage that may arise in the future. Accordingly, assurance is an important complement to liability rules, restoration obligations, and other regulatory compliance requirements. The paper reviews the need for assurance, given the prevalence of abandoned environmental obligations, and assesses the implementation of assurance rules in the United States. From the standpoint of both legal effectiveness and economic efficiency, assurance rules can be improved. On the whole, however, cost recovery, deterrence, and enforcement are significantly improved by the presence of existing assurance regulations.

Purpose: To analyse the insurance market breakthroughs through ‘Big Data’ and the possibility of new techniques of services provided, creating access for information gathering and fraud detection. This can contribute to improved risk management processes and mitigation strategies referred to as ‘InsurTech’.

Methodology: We catalogue the technique which is especially useful and being evaluated as having the ability to bring innovations to the insurance business. In doing this, we reveal which marketplaces actively participate in start-ups and how insurers engage in them and present them, highlighting the impact of blockchain technology, ride services, robo-advice, and data analysis on the insurance industry.

Findings: Findings show that because emerging economies have fewer organisation needs to ensure the distribution model, technology and research may significantly influence such areas. Nonetheless, whether industrialised or emergent, relevant legislative inspections should be carried out to protect subscribers’ welfare.

Practical implication: Since ‘Big Data’ impacts insurers’ constant monitoring of business risks and corporate governance, an overview of how information is harnessed should be carefully studied. Moreover, it is essential to study the handling of algorithms to guarantee that the expectations are reasonable and that unforeseen effects are avoided to the greatest extent feasible, and regulators have a mechanism for engaging in this review.

The Bureau of Economics in the Federal Trade Commission has a three-part role in the Agency and the strength of its functions changed over time depending on the preferences and ideology of the FTC’s leaders, developments in the field of economics, and the tenor of the times. The over-riding current role is to provide well considered, unbiased economic advice regarding antitrust and consumer protection law enforcement cases to the legal staff and the Commission. The second role, which long ago was primary, is to provide reports on investigations of various industries to the public and public officials. This role was more recently called research or “policy R&D”. A third role is to advocate for competition and markets both domestically and internationally. As a practical matter, the provision of economic advice to the FTC and to the legal staff has required that the economists wear “two hats,” helping the legal staff investigate cases and provide evidence to support law enforcement cases while also providing advice to the legal bureaus and to the Commission on which cases to pursue (thus providing “a second set of eyes” to evaluate cases). There is sometimes a tension in those functions because building a case is not the same as evaluating a case. Economists and the Bureau of Economics have provided such services to the FTC for over 100 years proving that a sub-organization can survive while playing roles that sometimes conflict. Such a life is not, however, always easy or fun.

Introduction: New ideas and concepts of big data have emerged in recent years in response to the astounding growth of data in many industries. Furthermore, the phenomenal increase in the use of the internet and social media has added enormous amounts of data to conventional data processing systems. Still, it has also created challenges for traditional data processing.

Purpose: A significant characteristic of the insurance sector is critically dependent on information. This sector generates a great deal of structured and unstructured data, which traditional data processing techniques cannot handle. As compared to conventional insurance data processing and decision-making requirements, this lesson shows an analysis of data technology’s value additions.

Research methodology: The author assesses the primary use of cases for data in the insurance industry via a case study analysis. From the perspective of the insurance sector, this chapter examines the concepts, technologies, and tools of big data. A few analytical reviews by the insurance company are also provided, which justified several gains gained either through inefficient processing of massive, diverse data sets or by supporting better decisions.

Findings: This chapter demonstrates the importance of adopting new business models that allow insurers to move beyond understand and protect and become more predictive and preventative by using the tools and technologies of big data technology.

Purpose: Blockchain is the most significant technological innovation of the generation following the internet. However, most individuals are unaware of how it will affect the insurance business.

Design/methodology/approach: The present study utilises a systematic review methodology to assess the existing literature on blockchain technology in the insurance industry.

Findings: Currently, few insurance companies are researching and using blockchain technology for automated claims, fraud detection, and cash flow tracking. The use of blockchain technology in the insurance business is still in its early stages, and many significant issues remain unsolved. This chapter lays out the discussions regarding the current state of blockchain technology in the insurance business.

Practical implications: Using distributed ledger technology (DLT), all the stakeholders can easily exchange the relevant information on a real-time basis. In particular, blockchain technology will help all insurance companies minimise discrepancies related to fraudulent claims by keeping track of the customer’s history of the customer reducing administrative costs.

Originality/value: It has been observed that very few studies have been conducted in this field. This is a holistic study that focuses on the applications of blockchain technology in various non-life insurance segments.

Prior to widespread social insurance, European governments experimented with a variety of programs to protect workers from income loss due to illness. This paper examines the consequences for worker absenteeism of making sickness insurance coverage voluntary or compulsory. Medical benefits appear to have reduced absenteeism for all workers. The effect of paid sick leave depended on insurance fund membership status. Better-paid workers found it easier to take time off in compulsory than in voluntary funds. Distinctive information problems plagued voluntary systems, and eventually were resolved by rejecting the voluntary ideal and forcing all workers into a single risk pool.

Introduction: The internet of things (IoT) is the emerging technology of interconnected objects that can be termed as ‘things’ used to exchange data, connecting with different devices on the internet. It is the future where connected devices are controlled remotely. The insurance sector is one of the leading industries providing financial protection services to their customers to recover losses. Like others, the insurance industry uses the services very efficiently to solve their customer-centric problems and provide the best services to them. IoT in insurance is enhancing customer services.

Purpose: To determine how the insurance industry utilises the different IoT technologies to provide the best services and solutions to their users. The insurance sector is working on other areas of expertise to offer outstanding facilities to their clientele.

Methodology: We reviewed published material covering five years on IoT and insurance and customer services in the media, newspapers, journal publications, and the web. We determined how the insurance sector adapted the new terminology to contribute its best services to the users.

Findings: We observed that IoT services and technologies benefit the insurance industry and the clientele. This shows excellent results in the growth of the sector and heightened facilities for the consumers.

Purpose: This chapter sets out to lay out and analyse the effectiveness of the General Data Protection Regulation (GDPR), a recently established European Union (EU) regulation, in the local insurance industry.

Methodology: This was done through a systematic literature review to determine what has already been done and then a survey as a primary research tool to gather information. The survey was aimed at clients and employees of insurance entities.

Findings: The general results are that effectiveness can be segmented into different factors and vary regarding the respondents’ confidence. Other findings include that the GDPR has increased costs, and its expectations are unclear. These findings suggest that although the GDPR was influential in the insurance market, some issues about this regulation still exist.

Conclusions: GDPR fulfils its purposes; however, the implementation process of this regulation can be facilitated if better guidelines are issued for entities to follow to understand its expectations better and follow the law and fulfil its purposes most efficiently.

Practical implications: These conclusions imply that the GDPR can be improved in the future. Overall, as a regulation, it is suitable for the different member states of the EU, including small states like Malta.