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Product intervention power is introduced under the markets in financial instruments regulation (MiFIR) and packaged retail and insurance-based investment products (PRIIPs) Regulation for all EU Member States and gives National Competent Authorities (NCAs), European Securities and Markets Authority (ESMA), and European Banking Authority (EBA) powers to monitor financial products (and services) under their supervision and to “temporarily” prohibit or restrict the marketing, distribution, or sale of certain financial instruments, or to intervene in relation to certain financial activities or practice. This extends the supervisory measures defined in MiFID II to any PRIIPs (including insurance-based investment products “IBI products”) that would not otherwise fall under the scope of MiFID II. Product intervention power is given to the NCAs, and in order to use power, it requires to take the specifics of the individual case into account and a series of conditions, criteria, and factors to fulfill. Moreover, ESMA and the EBA have a type of control function and ability to override national regulators on product. The aim of product intervention powers is to ensure strengthening of investor protection, but given the potential significant impact of this power, calls into question of possibility to delay innovation and slow down product developments on the capital market.

This paper provided an overview of supervisory measures on product intervention, that is, scope of the product intervention power, criteria, factors, and risks which have to be taken into consideration when using this regulator’s tool.

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.

Introduction: With many new technologies requiring real-time data processing, cloud computing has become challenging to implement due to high bandwidth and high latency requirements.

Purpose: To overcome this issue, edge computing is used to process data at the network’s edge. Edge computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed. It is used to process time-sensitive data.

Methodology: The authors implemented the model using Linux Foundation’s open-source platform EdgeX Foundry to create an edge-computing device. The model involved getting data from an on-board sensor (on-board diagnostics (OBD-II)) and the GPS sensor of a car. The data are then observed and computed to the EdgeX server. The single server will send data to serve three real-life internet of things (IoT) use cases: auto insurance, supporting a smart city, and building a personal driving record.

Findings: The main aim of this model is to illustrate how edge computing can improve both latency and bandwidth usage needed for real-world IoT applications.

Purpose: This chapter aims to present the arguments for and against central bank digital currency (CBDC) increasing financial inclusion. Financial inclusion is one of the many reasons for issuing a CBDC.

Need for the study: There is a need to offer a critical perspective on the proposed financial inclusion benefits of CBDC. This is the first paper to present arguments supporting and statement against CBDC for financial inclusion.

Method: This chapter uses discourse analysis methodology to identify the arguments about CBDC promoting financial inclusion

Findings: The arguments in support of CBDC increasing financial inclusion are that CBDCs can digitise value chains, CBDCs can improve access to digital financial services, CBDCs can help to enlarge the digital economy, CBDCs can enhance the efficiency of digital payments, CBDCs can be used offline when there is no internet coverage, and CBDCs have low transaction costs. Some criticisms are that CBDC may not prioritise financial inclusion, a high price to purchase digital devices for holding a CBDC, non-interest-bearing CBDCs, the strong preference for cash over digital currency, the burdensome identification and regulatory requirements, and the imposition of transaction costs.

Implications: Overall, the arguments presented in this chapter show that there is still disagreement over whether a central bank’s digital currency can increase financial inclusion. Nevertheless, in the light of recent events, many central banks are determined to issue a CBDC for many reasons. Even though CBDCs do not achieve the intended financial inclusion objective, at least the other goals for publishing a CBDC will be performed, such as a significant reduction in cash management costs and the effective conduct of monetary policy.

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: This chapter aims to review the research literature on the insurance industry and map the emerging research trends in this field through a bibliometric analysis and network visualisation exercise.

Design/methodology/approach: The research literature gathered from the Web of Science (WoS) databases was applied to bibliometric analysis in this article. With the help of Biblioshiny, this research was utilised to identify documents, most prolific institutions, countries, resource titles, and WoS categories in the insurance industry. In addition, bibliometric mapping was used to identify national and institutional collaboration networks.

Findings: The author discovered that the literature had increased drastically in the academic discourse during the last two decades. According to the bibliometric data, developed countries such as the United States and the United Kingdom reign research in this sector. The research highlights the most prominent studies and writers in the insurance field and the evolution of the domain from its inception to the contemporary. It also highlights theoretical disagreements and contradictions between theoretical conceptualisation and empirical measures by presenting the significant concerns in the literature.

Originality/value: This chapter delivers the first comprehensive bibliometric analysis of the insurance sector’s literature production in connection to emerging technology, which will aid researchers and practitioners in better understanding the relationships between themes and outsiders to understand the domain area better. The author makes recommendations for future perspectives study directions and highlights the critical conceptual framework that can build future research. Overall, this research contributes to a better understanding of the insurance industry and offers new perspectives.

The area of law where the principle of transparency is applicable is expanding fast. Also many financial markets have recently become subject to new regulations requiring transparency, such as EU directives MIFID II or Solvency II. Here, what is expanding is not just the applicability of the principle as such, but also the scope of issues which are affected by transparency, that is, remuneration or conflict of interests. In the light of these regulations, it may seem that transparency has simply become a sole legislative measure assuring values such as consumer protection, market stability or – most of all – high-quality governance. Indeed, transparency is thought to contribute to the quality of governance in several different ways, although its implementation must meet certain standards if it is to produce the desired results, especially when it comes to financial institutions. Financial institutions are commonly required to be particularly transparent due to the fact they often act as public trust entities. As the activity of financial institutions is of such importance, the issue of transparency efficiency is worth discussing. Although it is said that the emergence of the principle of transparency in the EU law is a fairly new phenomenon, the existence of transparency obligation is not. Therefore, some doubts may arise as to the question whether the principle of transparency actually adds much to existing rules and principles. In this chapter the author explored and discussed how mandatory transparency affects financial institutions’ activity, and whether it performs its function efficiently.

In this chapter we investigated the importance of the Audit Statement of Opinion in the Final Audit Report to ensure good corporate governance and to reduce earnings management and ensure accurately informed corporate decisions. After going through literature and discussing with peers we hypothesized that this does have an effect on all the three processes.

A self-administered survey was purposely designed for the study after consulting the literature and referring to established frameworks and consulted with accounting executives. The survey consisted of an introduction page and four sections contained statements relating to each of the following four themes: “earnings management”; “audit statement and report”; “corporate governance”; and “the corporate decision.” For all statements, participants were asked to respond to a five-point Likert items ranging from “strongly disagree” (coded as “1”) to “strongly agree” (coded as “5”).

The research was conducted with a population of 100 accounting managers and financial managers of manufacture companies listed on Bursa Efek Indonesia (BEI) during 2015. To test the hypothesis, we used SPSS (Version 22) to carry out a regression analysis using the F and t tests.

It is determined that the three hypotheses were correct and the Audit Statement of Opinion in the Final Audit Report influences corporate governance and earning management reducing deviant behavior and that there is a significant reliance by Indonesians managers/investors on it when taking corporate decision.