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This book covers big data, machine learning, and artificial intelligence-related technologies and how these technologies can enable the design, development, and delivery of customer-focused financial services to both corporate and retail customers, as well as how to extend the benefits to the financially excluded sections of society. Artificial Intelligence, Fintech, and Financial Inclusion describes the applications of big data and its tools such as artificial intelligence and machine learning in products and services, marketing, risk management, and business operations. It also discusses the nature, sources, forms, and tools of big data and its potential applications in many industries for competitive advantage. The primary audience for the book includes practitioners, researchers, experts, graduate students, engineers, business leaders, and analysts researching contemporary issues in the area.
Recent advances in digital technology and big data have allowed FinTech (financial technology) lending to emerge as a potentially promising solution to reduce the cost of credit and increase financial inclusion. However, machine learning (ML) methods that lie at the heart of FinTech credit have remained largely a black box for the nontechnical audience. This paper contributes to the literature by discussing potential strengths and weaknesses of ML-based credit assessment through (1) presenting core ideas and the most common techniques in ML for the nontechnical audience; and (2) discussing the fundamental challenges in credit risk analysis. FinTech credit has the potential to enhance financial inclusion and outperform traditional credit scoring by (1) leveraging nontraditional data sources to improve the assessment of the borrower’s track record; (2) appraising collateral value; (3) forecasting income prospects; and (4) predicting changes in general conditions. However, because of the central role of data in ML-based analysis, data relevance should be ensured, especially in situations when a deep structural change occurs, when borrowers could counterfeit certain indicators, and when agency problems arising from information asymmetry could not be resolved. To avoid digital financial exclusion and redlining, variables that trigger discrimination should not be used to assess credit rating.
The emergence of financial technology (FinTech)-related products is causing major disruptions in financial services that enable financial solutions and innovative business models resulting in the fusion of finance and smart mobile technology. As ASEAN is undergoing a paradigm shift from government-to-government (G2G) to community-to-community (C2C) relationships with the emphasis on integration and collaboration, the adoption of FinTech and its possible future directions needs to be studied further. Financial Technology and Disruptive Innovation in ASEAN provides an assortment of innovative research that explores the recent FinTech initiative in ASEAN with respect to its process, strategies, challenges, and outcomes and highlights new business models, products, and services that affect financial markets and institutions and the provision of financial services. While highlighting topics including blockchain technology, cloud computing, and mobile banking, this book is ideally designed for business executives, managers, entrepreneurs, financial and banking practitioners, policymakers, academicians, students, professionals, and researchers.
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
Technology is changing the landscape of the financial sector, increasing access to financial services in profound ways. These changes have been in motion for several years, affecting nearly all countries in the world. During the COVID-19 pandemic, technology has created new opportunities for digital financial services to accelerate and enhance financial inclusion, amid social distancing and containment measures. At the same time, the risks emerging prior to COVID-19, as digital financial services developed, are becoming even more relevant.
Microfinance is a renowned albeit controversial solution for giving financial access to the unbanked, even if micro-transactions increase costs, limiting outreach potential. The economic and financial sustainability of Microfinance Institutions (MFIs) is a prerequisite for widening a potentially unlimited client base. Automation decreases costs, expanding the outreach potential, and improving transparency and efficiency. Technological solutions range from branchless mobile banking to geo-localization of customers, digital/social networking for group lending, blockchain validation, big data, and artificial intelligence, up to “MicroFinTech” - FinTech applications adapted to microfinance. Of interest to both scholars, students, and professors of financial technology and microfinance, this book examines these trendy solutions comprehensively, going beyond the existing literature and showing potential applications to the traditional sustainability versus outreach trade-off.
This book, written jointly by an engineer and artificial intelligence expert along with a lawyer and banker, is a glimpse on what the future of the financial services will look like and the impact it will have on society. The first half of the book provides a detailed yet easy to understand educational and technical overview of FinTech, artificial intelligence and cryptocurrencies including the existing industry pain points and the new technological enablers. The second half provides a practical, concise and engaging overview of their latest trends and their impact on the future of the financial services industry including numerous use cases and practical examples. The book is a must read for any professional currently working in finance, any student studying the topic or anyone curious on how the future of finance will look like.
This collection critically explores the use of financial technology (FinTech) and artificial intelligence (AI) in the financial sector and discusses effective regulation and the prevention of crime. Focusing on crypto-assets, InsureTech and the digitisation of financial dispute resolution, the book examines the strategic and ethical aspects of incorporating AI into the financial sector. The volume adopts a comparative legal approach to: critically evaluate the strategic and ethical benefits and challenges of AI in the financial sector; critically analyse the role, values and challenges of FinTech in society; make recommendations on protecting vulnerable customers without restricting financial innovation; and to make recommendations on effective regulation and prevention of crime in these areas. The book will be of interest to teachers and students of banking and financial regulation related modules, researchers in computer science, corporate governance, and business and economics. It will also be a valuable resource for policy makers including government departments, law enforcement agencies, financial regulatory agencies, people employed within the financial services sector, and professional services such as law, and technology.
Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important
FinTech is a major force shaping the structure of the financial industry in sub-Saharan Africa. New technologies are being developed and implemented in sub-Saharan Africa with the potential to change the competitive landscape in the financial industry. While it raises concerns on the emergence of vulnerabilities, FinTech challenges traditional structures and creates efficiency gains by opening up the financial services value chain. Today, FinTech is emerging as a technological enabler in the region, improving financial inclusion and serving as a catalyst for the emergence of innovations in other sectors, such as agriculture and infrastructure.