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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.

Insurance in Malta has been very largely influenced by English practice and law. The influence of the English market insurance practice and law not only shaped the Maltese market but practically that of all common law jurisdictions in former members of the British empire. Since the London insurance market continues to be a very dominant force globally until today, the connection has undoubtedly served Malta well.

The origins of UK insurance principles of utmost good faith and insurable interest under contract law, date back to times which were very different from today and the need to revise the laws has now been felt in the UK as well as in other jurisdictions which were influenced by its law and practice. In Malta, minimal legislative intervention and the Maltese courts were and continue to be mostly guided by English case law, some of which has now been superseded by the updated statute law which was recently introduced in the UK by virtue of the Consumer Insurance (Disclosure and Representations) Act (2012) and Insurance Act (2015).

We herein lay out a case study of the development of utmost good faith and insurable interest in insurance contracts within the Maltese legal context, based on empirical literature findings and semi-structured interviews together with several legal experts who are specialized in the field and experienced insurance professionals.

Insurance is a contract whereby one party (the policyholder) promises and makes a payment or series of payments in exchange for the second party’s (the insurance company’s) promise to indemnify the policyholder for losses covered under the terms of the policy. Perhaps it is easier to just think of insurance as a transaction where the policyholder trades small regular losses (the premium paid) for large and irregular gains (claims proceeds).

While it may seem somewhat disproportionate to devote an entire chapter to more detailed treatment of a single risk financing tool, insurance has a very large impact, not only in terms of its intrinsic value, but also in terms of the many ways in which insurance influences risk management thinking and practice. As will be shown, some of this influence is waning and in other cases it could be argued that insurance ‘thinking’ has hindered efforts to respond to facts on the ground and the ability to adapt the role of risk management in organisations.

To provide a useful discussion, this chapter will cover both the products that the insurance industry offers and the structure of the industry itself, along with addressing legal and regulatory matters that were touched upon in Chapter Nine. The chapter concludes with an overview of public sector insurance issues that provides a basis for understanding alternatives to insurance that have emerged in dramatic fashion in recent decades – which in turn provides a basis for considering some of the constraints that insurance imposes on risk management practice.

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.

Purpose: The scope of this research is to conduct a study on the perceived effectiveness of developments in InsurTech, by determining online use integration in the Maltese insurance market.

Methodology: To do this, the authors employed a self-administered questionnaire to which 471 participants responded on a 5-point Likert scale. We subjected the data collected from this questionnaire to statistical analysis, specifically, exploratory factor analysis (EFA) and multiple linear analysis using the Statistical Package for Social Science (SPSS) version 26.

Results: EFA loaded best on five factors of insurance customers’ perceived effectiveness, which make up the effectiveness model (EM), namely ‘Factor 1 – Internal Process Enhancement’, ‘Factor 2 – Cost-Efficiencies’; ‘Factor 3 – Time-Sensitive Conditions’, ‘Factor 4 – The Contemporary Use of Artificial Intelligence and Marketing in Relation to Customer Service’ and ‘Factor 5 – Customer Relations and Application of InsurTech in Communication’. Moreover, multiple linear regression results show that the perceived effectiveness dimension – EM is statistically significantly related to online use in Malta.

Practical implications: Therefore, it can be argued that the Maltese insurance sector is well prepared to meet the obligations and requirements of the European Green Deal. Findings shed light on the preparedness of the Maltese insurance market to accept innovative green proposals to go online with processes.

Insurance frauds deeply affect insurance companies, policyholders, and the insurance industry as a whole. The cost of fraudulent damage affects the profitability of companies, and has negative effects on the society in terms of moral values. Increases in insurance costs can lead to increases in the premiums paid by policyholders, each family, and, ultimately, all of the insured. Recently, new legal regulations related to this issue have been performed in Turkey and higher institutions have been created. A regulation issued by the Under-secretariat of the Treasury, on June 1, 2011, defines insurance fraud as aggravated fraud. Insurance fraud in Turkey usually takes the form of intentional misrepresentations of facts to the insurance company to get the company to pay for something not actually covered by the policy. Studies examined the insurance industry in terms of the concept of financial crime, and inclusion of the concept of financial crime in insurance regulations was proposed since financial crimes have an important place in the current problems of the industry. In addition, it is seen that insurance frauds have changed over time as a result of studies.

Introduction: The insurance sector is playing a crucial role in the sustainable growth of the Indian economy. But in India, this sector loses crores of rupees every year due to the increasing fraud cases. With the increase in insurance customers, insurance companies need to efficiently equip themselves with a robust system to handle claims fraud. Detection of insurance fraud is a pretty challenging problem. Nowadays, machine learning (ML) and artificial intelligence (AI) are the strategic choices of many leading organisations that want to proceed in a new digital arena.

Purpose: This chapter’s main objective is to highlight the fundamental market forces driving the adoption of AI and ML and showcase the traditional and modern methods to predict insurance claims fraud intelligently.

Methodology: Various research papers have been reviewed, and ML methods have been discussed, which are all being used to predict insurance fraud claims. This chapter also highlights various driving forces influencing the adoption of ML.

Findings: This study highlights the introduction of blockchain technology in fraud detection and in combatting insurance fraud. Literature indicates that the quantity and quality of data significantly impact predictive accuracy. ML models are beneficial to identify the majority of fraudulent cases with reasonable precision. Insurance companies should explore the benefits of experienced resource persons from the same domain and develop unique business ideas/rules.

The second major area of the so-called risk treatment is risk financing. Risk financing includes measures to finance the costs of losses, risks, and uncertainties. Historically, risk financing has been virtually synonymous with buying insurance. However, over time alternatives to insurance have evolved – self-insurance, pools, captives, large deductible programmes, finite insurance programmes, banking arrangements, and capital market-based solutions. The concept of risk financing has expanded to include products that address a range of financial risks such as interest rate and credit risk. These products include derivatives and some new innovative securities.

Today, the rapid development of the risk financing market has created several practical problems. Notably, regulatory and legal structures have not always kept pace with change, leading to much confusion about risk financing alternatives. Many products look and function almost identically to others, and yet history and custom have dictated very different treatment by regulators, tax authorities, and others. There is growing pressure for significant legal and regulatory realignment.

For newcomers to the field, risk financing measures can be thought of as existing on a continuum, ranging from pure retention (all losses paid directly out of pocket) to pure transfer (where a third party accepts and bears the full costs of risk). An important recognition of the continuum of risk financing is that there are no products that are fully retention or transfer, but rather a varying blend of the two. Hedging of risk, for example, is arguably here a near perfect blending of a retention and a transfer of risk.