Catálogo de publicaciones - libros

Crowdfunding is one of the funding sources that entrepreneurs are increasingly being exposed to above and beyond venture capital and angel funding. After introducing the most popular crowdfunding types, this chapter proceeds to present and compare the evolution of the phenomenon across three macro regions: Europe, USA, and Asia-Pacific. Furthermore, the chapter offers an overview of the state-of-the-art of the crowdfunding literature, highlighting creators’ and funders’ incentives and disincentives for starting or engaging in crowdfunding projects, the characteristics of a successful campaign, and the contextual factors that explain the evolution of the phenomenon across countries. The chapter closes providing suggestions for future work in this area.

Digital technologies are transforming how small businesses access finance and from whom. This chapter explores online peer-to-peer (P2P) lending, a form of crowdfunding that connects borrowers and lenders. Information asymmetry is a key issue in online peer-to-peer lending marketplaces that can result in moral hazard or adverse selection, and ultimately impact the viability and success of individual platforms. Both online P2P lending platforms and lenders seek to minimise the impact of information asymmetries through a variety of mechanisms. This chapter discusses the structure of online P2P lending platforms and reviews how the disclosure of hard and soft information, and herding can reduce information asymmetries. The chapter concludes with a discussion of further avenues for research.

We explore how machine learning and artificial intelligence (AI) solutions are transforming risk management. A non-technical overview is first given of the main machine learning and AI techniques of benefit to risk management. Then a review is provided, using current practice and empirical evidence, of the application of these techniques to the risk management fields of credit risk, market risk, operational risk, and compliance (‘RegTech’). We conclude with some thoughts on current limitations and views on how the field is likely to develop in the short- to medium-term. Overall, we present an optimistic picture of the role of machine learningand AI in risk management, but note some practical limitations around suitable data management policies, transparency, and lack of necessary skillsets within firms.

This chapter provides a review on key literature on High-Frequency Trading (HFT) over an 11-year period. Using a thematic analysis, the main themes developed within this research stream are identified and insights on the evolution of theory in relation to HFT are presented. This analysis highlights that the effects of HFT on market liquidity, trading strategies and speed, implications for market structure changes, and the relationship between the “scriptability” of corporate disclosure and HFT short-term information advantage, are key themes. The analysis also suggests that many open questions remain unanswered including more recent HFT trading strategies and complex techniques applied to analyse the content of both voluntary and mandatory corporate disclosure. As capital markets evolve, HFT’s speed may no longer be sufficient to maintain competitiveness. The chapter concludes with a discussion of future trends and areas for research on HFT.

Traditional challenges insurers face include: (1) asymmetric information—the inability to price a policyholder correctly; (2) moral hazards—the change of attitude following cover; and (3) claims management. In this chapter, we discuss how disruptive technologies are evolving in the insurance sector and the challenges faced in their implementation. We show how large and continuous datasets are transforming the general insurance markets and their business processes, as well as enticing desirable policyholder behaviour and streamlining claims management. We then discuss how artificial intelligence is improving traditional insurance processes from the first point of contact to claims management. We also examine the use of artificial intelligence as a means of interacting with prospective clients and existing policyholders. Finally, we explain how blockchain technology can transform the structure of the insurance market to a peer-to-peer format.

This chapter explores the promise and potential of Regulatory Technologies (RegTech), a new and vital dimension to FinTech. It draws on the findings and outcomes of a five-year research programme to highlight the role that RegTech can play in making regulatory compliance more efficient and effective. The chapter presents research on the Bank of England/Financial Conduct Authority (FCA) RegTech Sprint initiative, whose objective was to demonstrate how straight-through processing of regulations and regulatory compliance reporting using semantically enabled applications can be made possible by RegTech. The chapter notes that the full benefits of RegTech will only materialise if the pitfalls of a fragmented Tower of Babel approach are avoided. Semantic standards, we argue, are the key to all this.

The EU required member states to implement the new Payment Services Directive (PSD II) by January 2018. The European Banking Authority (EBA) will provide important final guidance on areas such as security during 2018, which will need to be implemented over the following couple of years. The increase in mobile and Internet banking and the failure of the original 2007 first Payment Services Directive (PSD I) to develop cross-border payment services encouraged the development of the revised Directive. The EU also took the opportunity to assist the development of new payment services, which may, in due course, disintermediate some of the traditional payment arrangements including, for example, those provided by credit card companies, and to reduce the cost of payments services for, primarily, businesses. It will pose challenges for banks and present opportunities for both new FinTech operations and large firms such as Apple and Amazon. The full benefits of the new Directive will only be gained if a critical mass of customers see the value of the new services and trust the firms and processes involved.

In our highly connected world, the number of digital transactions is growing, and so too are the myriad of digital platforms that enable these transactions. While the dominant perspective on developing digital payment platforms involves implementing an efficient, low cost, and secure transfer of value, in this chapter, we take a step back to re-examine how digital transactions are embedded in social relationships, and that by focusing solely on the transfer of value, it is possible to miss opportunities for social interactions in digital transactions. We examine the affordances of digital transactions to illustrate possibilities for action, opportunities for interaction, and the roles of negotiation and intermediation within digital transactions. We then highlight some social impacts of digital transactions and its associated data generation, its embeddedness alongside other available forms of transaction, and the ways in which the digital world conflates money with payment systems.

Crypto assets can be classified into two main categories, according to their principal function: native coins and crypto tokens. Native coins, like Bitcoin, generally compete with the traditional forms of money providing both an alternative currency instrument and a payment infrastructure. Differently from native coins, crypto tokens are coins that embed some intrinsic values somehow linked to the quality of the issuing entity’s business model and to the ecosystem it generates. This chapter explores the emergent start-up token funding model of Initial Coin Offering, which allows entrepreneurs to bypass the traditional capital market by issuing crypto tokens directly to investors. The positive feedback loop between an issuer’s business model and the token funding model will be demystified.

It is claimed that blockchain technology has the potential to revolutionise how financial services firms conduct their business. This chapter presents the main characteristics of blockchain technology and summarises the extant research around the potential implications of blockchain adoption for four main financial activities: payments and remittance, credit and lending, trading and settlement, and compliance. Current gaps in the literature are discussed in order to identify avenues for future research.