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Current trends in financial services are characterised by two intertwined developments. First, increasing digitalisation provides opportunities to invest or raise money through channels that have not been available with more traditional financial services. Crowd-investing and social-trading platforms act as new intermediaries. Similarly, automated advice (robo-advice) is attracting increased attention. Second, the financial crisis of 2007–2010 is associated with a considerable decline in trust in financial institutions, even more so in Iceland, which had experienced a complete collapse of its banking system. Despite the evaporation of trust in their banking system, Icelandic consumers were largely bound to use Icelandic financial institutions because capital controls were in place since the financial crisis until 2017, which limited investors’ opportunities to, for example, diversify their portfolios internationally. As financial decisions are inherently risky and since financial services have the characteristics of credence goods, those who wish to use financial services need to trust financial intermediaries or the immediate contractual partner. The purpose of this chapter is to examine the role of trust in the context of increased digitalisation, and to discuss steps to establish trust in digitalised financial services. Among other items, we discuss the information requirements accompanying financial products and financial institutions, data protection and liability in the context of emerging digitalisation. Our work holds implications for individuals, financial service providers, policy makers and supervisory authorities.

This conceptual paper explores the implications for the sociology of the professions of robo-advice (RA) provided by robo-advisors (RAs) as an early example of successfully programmed algorithmic knowledge managed by artificial intelligence (AI).

The authors examine the drivers of RAs, their success, characteristics, and establish RA as an early precursor of commercialized, programmed professional advice with implications for developments in the sociology of the professions.

Within the lens of the sociology of the professions, the success of RAs suggests that the diffusion of this innovation depends on three factors: the programmed flows of automated professional knowledge are minimally disruptive, they are less costly, and attract attention because of the “on-trend” nature of algorithmic authority guided by AI. The on-trend nature of algorithmic governance and its increasing public acceptance points toward an algorithmic paradox. The contradictions arise in the gap between RA marketed to the public and as a set of professional practices.

The incursion of RA-like disembodied advice into other professions is predicted given the emergence of tech-savvy clients, the tie between RA and updatable flows of big data, and an increasing shift to the “maker” or “do-it-yourself” movements.

Using the success of RAs in the financial industry, the authors predict that an AI-managed platform, despite the algorithmic paradox, is an avenue for growth with implications for researchers in the sociology of the professions.

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 purpose of this paper is to review the effect of reforms to the UK’s retail advice sector as a result of the Retail Distribution Review (RDR).

The paper takes the form of a review of the RDR in the context of the Financial Advice Market Review (FAMR).

There is a lack of clarity, experienced by both consumers and financial advisers, concerning the nature of “advice”. This results from the use of an array of regulatory and non-regulatory terms. Whilst enhancing professionalisation and reducing commission bias, the RDR is failing to address the needs of many financial consumers – identified by many as an “advice gap”. It is argued that the focus of the RDR, and previous reforms, on addressing market failures may be misplaced.

The paper provides an analysis designed to help in the process of developing a retail advice sector that meets the needs of consumers, in the context policy reforms placing more emphasis on the responsibilities of individuals for financial planning.

The study has the potential of better outcomes for consumers and reputational returns for the financial services sector.

This paper is a review of the current regulatory issues facing financial advisers and retail consumers in the context of the RDR and FAMR.

In the context of increasing private provision of social security and welfare, alongside what is argued to be the ‘financialisation’ of daily lives, individuals in many countries face an array of potentially difficult financial choices and decisions. Limitations in levels of knowledge and expertise may lead them to consider seeking financial advice. Yet, in the wake of the great financial crisis, trust in the financial services industry is low.

At the same time, in a number of countries the financial advice sector is facing its own challenges. These include regulatory issues concerning the definition, suitability and delivery of advice; the affordability of advice; and the challenges and opportunities facing the advice sector as a result of the increasing use of technology in the financial services sector.

This chapter examines the implications of these developments for the regulation and governance of financial advice in the context of Markets in Financial Instruments Directive II. In particular, it considers the example of the UK and issues this raises for the implementation of recent European regulatory reforms.

AI-based robo-advisory (RA) represents a FinTech application that is already replacing retail investment advisors. In private banking (PB), clients also increasingly expect service provision across different digital channels, but with a higher degree of personalization. Hence, the present study investigates the impact of intelligent RA on the PB investment advisory process to derive both process (re)design knowledge and strategic guidance for artificial intelligence (AI) usage for PB investment advisory.

The present study applies an AI process impact analysis approach by decomposing AI-based RA into three AI application types: conversational agent, customer segmentation and predictive analytics. The analysis results along a reference PB investment advisory process reveal sub-process transformations which are applied for process redesign integrating AI.

The study results imply that AI systems (1) enable seamless client journeys, (2) increase advisor flexibility, (3) support the client–advisor relationship by applying an omnichannel approach and (4) demand advisor skills to be augmented with technical and statistical knowledge.

The research study contributes (1) an AI process impact analysis approach, (2) derives process (re)design knowledge for AI deployment and (3) develops strategic guidance for AI usage in PB investment advisory.

The objective of this study is to provide a systematic review of the literature on artificial intelligence (AI) in customer-facing financial services, providing an overview of explored contexts and research foci, identifying gaps in the literature and setting a comprehensive agenda for future research.

Combining database (i.e. Scopus, Web of Science, EBSCO, ScienceDirect) and manual journal search, the authors identify 90 articles published in Australian Business Deans Council (ABDC) journals for investigation, using the TCCM (Theory, Context, Characteristics and Methodology) framework.

The results indicate a split between data-driven and theory-driven research, with most studies either adopting an experimental research design focused on testing the accuracy and performance of AI algorithms to assist with credit scoring or investigating AI consumer adoption behaviors in a banking context. The authors call for more research building overarching theories or extending existing theoretical perspectives, such as actor networks. More empirical research is required, especially focusing on consumers' financial behaviors as well as the role of regulation, ethics and policy concerned with AI in financial service contexts, such as insurance or pensions.

The review focuses on AI in customer-facing financial services. Future work may want to investigate back-office and operations contexts.

The authors are the first to systematically synthesize the literature on the use of AI in customer-facing financial services, offering a valuable agenda for future research.

Purpose: The goal of this study is to delve into the causes behind the Fintech sector’s rise in various areas and its prospects. Fintech is rapidly expanding because of government legislation, multiple schemes, consumer expectations, a cashless economy, digitisation, globalisation, innovation, and other drivers.

Need for the Study: Fintech firms are forming alliances with traditional financial organisations to stay afloat and compete. India is becoming a superpower regarding e-startups, especially unicorns. Many startups are undergoing initial public offerings (IPOs). Fintech is an emerging space in India, spreading its wings rapidly in every sector.

Methodology: This work is based on a literature review. It utilises secondary data from numerous research publications, magazines, newspapers, published reports, relevant websites, Forbes magazine articles, stories from The Economic Times, the RBI Portal, and information from StartupIndia, Assocham, and Pwc, among others, to develop a conceptual framework showing the growth drivers of Fintech.

Findings: The whole world has been affected severely due to COVID-19. Crisis always comes with some opportunity, and it is up to us how to turn the calamities into opportunities that further turn into innovation that has the power to lead the world. Fintech is that fruit that had been born normally but grew abnormally (tremendous growth) during the pandemic. Also, the roots are so deeper that they will flourish more and more. It has been found that the emergence of a cashless economy, ease of internet connectivity, etc., are the major factors that paved the way for growth for Fintech in India.

Practical Implications: This study contains the conceptual framework which can guide the stakeholders, policymakers, management teams, field experts, etc., in knowing about their area expertise and looking for improvement, if any.

Originality: There are many papers on the relationship between Fintech and financial inclusion, but this is the first study that builds the conceptual framework for the growth drivers of Fintech.