Download or read book FinTech in Financial Inclusion Machine Learning Applications in Assessing Credit Risk written by Majid Bazarbash and published by International Monetary Fund. This book was released on 2019-05-17 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Artificial Intelligence Fintech and Financial Inclusion written by Rajat Gera and published by CRC Press. This book was released on 2023-12-29 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Fintech Credit Risk Assessment for SMEs Evidence from China written by Yiping Huang and published by . This book was released on 2020-09-25 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: Promoting credit services to small and medium-size enterprises (SMEs) has been a perennial challenge for policy makers globally due to high information costs. Recent fintech developments may be able to mitigate this problem. By leveraging big data or digital footprints on existing platforms, some big technology (BigTech) firms have extended short-term loans to millions of small firms. By analyzing 1.8 million loan transactions of a leading Chinese online bank, this paper compares the fintech approach to assessing credit risk using big data and machine learning models with the bank approach using traditional financial data and scorecard models. The study shows that the fintech approach yields better prediction of loan defaults during normal times and periods of large exogenous shocks, reflecting information and modeling advantages. BigTech's proprietary information can complement or, where necessary, substitute credit history in risk assessment, allowing unbanked firms to borrow. Furthermore, the fintech approach benefits SMEs that are smaller and in smaller cities, hence complementing the role of banks by reaching underserved customers. With more effective and balanced policy support, BigTech lenders could help promote financial inclusion worldwide.
Download or read book The Promise of Fintech written by Ms.Ratna Sahay and published by International Monetary Fund. This book was released on 2020-07-01 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Powering the Digital Economy Opportunities and Risks of Artificial Intelligence in Finance written by El Bachir Boukherouaa and published by International Monetary Fund. This book was released on 2021-10-22 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Download or read book Fintech and Financial Inclusion in Latin America and the Caribbean written by Mr. Dmitry Gershenson and published by International Monetary Fund. This book was released on 2021-08-20 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite some improvement since 2011, Latin America and the Caribbean continue to lag behind other regions in terms of financial inclusion. There is no clear evidence that fintech developments have supported greater financial inclusion in LAC, contrary to what has been observed elsewhere in the world. Case studies by national policy experts suggest that barriers to entry in the financial sector, along with a constraining regulatory environment, may have hindered a faster adoption of fintech. However, fintech development seems to have accelerated in the wake of the COVID-19 pandemic and with the support of recent policy initiatives.
Download or read book FinTech in Sub Saharan African Countries written by Mr.Amadou N Sy and published by International Monetary Fund. This book was released on 2019-02-14 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book The Promise of Fintech written by Ms.Ratna Sahay and published by International Monetary Fund. This book was released on 2020-07-01 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Fintech Inclusive Growth and Cyber Risks Focus on the MENAP and CCA Regions written by Ms.Inutu Lukonga and published by International Monetary Fund. This book was released on 2018-09-11 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial technology (fintech) is emerging as an innovative way to achieve financial inclusion and the broader objective of inclusive growth. Thus far, fintech in the MENAP and CCA remains below potential with limited impact on financial inclusion. This paper reviews the fintech landscape in the MENAP and CCA regions, identifies the constraints to the growth of fintech and its contribution to inclusive growth and considers policy options to unlock the potential.
Download or read book The Future of Finance written by Henri Arslanian and published by Springer. This book was released on 2019-07-15 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Central Bank Risk Management Fintech and Cybersecurity written by Mr. Ashraf Khan and published by International Monetary Fund. This book was released on 2021-04-23 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on technical assistance to central banks by the IMF’s Monetary and Capital Markets Department and Information Technology Department, this paper examines fintech and the related area of cybersecurity from the perspective of central bank risk management. The paper draws on findings from the IMF Article IV Database, selected FSAP and country cases, and gives examples of central bank risks related to fintech and cybersecurity. The paper highlights that fintech- and cybersecurity-related risks for central banks should be addressed by operationalizing sound internal risk management by establishing and strengthening an integrated risk management approach throughout the organization, including a dedicated risk management unit, ongoing sensitizing and training of Board members and staff, clear reporting lines, assessing cyber resilience and security posture, and tying risk management into strategic planning.. Given the fast-evolving nature of such risks, central banks could make use of timely and regular inputs from external experts.
Download or read book Fintech in Latin America and the Caribbean Stocktaking written by Pelin Berkmen and published by International Monetary Fund. This book was released on 2019-03-26 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Latin America and the Caribbean (LAC), financial technology has been growing rapidly and is on the agenda of many policy makers. Fintech provides opportunities to deepen financial development, competition, innovation, and inclusion in the region but also creates new and only partially understood risks to consumers and the financial system. This paper documents the evolution of fintech in LAC. In particular, the paper focuses on financial development, fintech landscape for domestic and cross border payments and alternative financing, cybersecurity, financial integrity and stability risks, regulatory responses, and considerations for central bank digital currencies.
Download or read book Machine Learning for Finance written by Saurav Singla and published by BPB Publications. This book was released on 2021-01-05 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand the essentials of Machine Learning and its impact in financial sector KEY FEATURESÊ _Explore the spectrum of machine learning and its usage. _Understand the NLP and Computer Vision and their use cases. _Understand the Neural Network, CNN, RNN and their applications. _ÊUnderstand the Reinforcement Learning and their applications. _Learn the rising application of Machine Learning in the Finance sector. Ê_Exposure to data mining, data visualization and data analytics. DESCRIPTION The fields of machining adapting, profound learning, and computerized reasoning are quickly extending and are probably going to keep on doing as such for a long time to come. There are many main impetuses for this, as quickly caught in this review. Now and again, the advancement has been emotional, opening new ways to deal with long-standing innovation challenges, for example, progresses in PC vision and picture investigation.Ê Ê The book demonstrates how to solve some of the most common issues in the financial industry.Ê The book addresses real-life problems faced by practitioners on a daily basis. The book explains how machine learning works on structured data, text, and images. You will cover the exploration of Nave Bayes, Normal Distribution, Clustering with Gaussian process, advanced neural network, sequence modeling, and reinforcement learning. Later chapters will discuss machine learning use cases in the finance sector and the implications of deep learning. The book ends with traditional machine learning algorithms. Ê Machine Learning has become very important in the finance industry, which is mostly used for better risk management and risk analysis. Better analysis leads to better decisions which lead to an increase in profit for financial institutions. Machine Learning to empower fintech to make massive profits by optimizing processes, maximizing efficiency, and increasing profitability. WHAT WILL YOU LEARN _ Ê Ê Ê You will grasp the most relevant techniques of Machine Learning for everyday use. _ Ê Ê Ê You will be confident in building and implementing ML algorithms. _ Ê Ê Ê Familiarize the adoption of Machine Learning for your business need. _ Ê Ê Ê Discover more advanced concepts applied in banking and other sectors today. _ Ê Ê Ê Build mastery skillset in designing smart AI applications including NLP, Computer Vision and Deep Learning. WHO THIS BOOK IS FORÊ Data Scientist, Machine Learning Engineers and Individuals who want to adopt machine learning in the financial domain. Practitioners are working in banks, asset management, hedge funds or working the first time in the finance domain. Individuals who want to learn about applications of machine learning in finance or individuals entering the fintech domain. TABLE OF CONTENTS 1.Introduction 2.Naive Bayes, Normal Distribution and Automatic Clustering Processes 3.Machine Learning for Data Structuring 4.Parsing Data Using NLP 5.Computer Vision 6.Neural Network, GBM and Gradient Descent 7.Sequence Modeling 8.Reinforcement Learning For Financial Markets 9.Finance Use Cases 10.Impact of Machine Learning on Fintech 11.Machine Learning in Finance 12.eKYC and Anti-Fraud Policy 13.Uses of Data Mining and Data Visualization 14.Advantages and Disadvantages of Machine Learning 15.Applications of Machine Learning in Other Industries 16.Ethical considerations in Artificial Intelligence 17.Artificial Intelligence in Banking 18.Common Machine Learning Algorithms 19.Frequently Asked Questions
Download or read book MicroFinTech written by Roberto Moro-Visconti and published by Springer Nature. This book was released on 2021-09-06 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Understanding Cybersecurity Management in FinTech written by Gurdip Kaur and published by Springer Nature. This book was released on 2021-08-04 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book uncovers the idea of understanding cybersecurity management in FinTech. It commences with introducing fundamentals of FinTech and cybersecurity to readers. It emphasizes on the importance of cybersecurity for financial institutions by illustrating recent cyber breaches, attacks, and financial losses. The book delves into understanding cyber threats and adversaries who can exploit those threats. It advances with cybersecurity threat, vulnerability, and risk management in FinTech. The book helps readers understand cyber threat landscape comprising different threat categories that can exploit different types of vulnerabilties identified in FinTech. It puts forward prominent threat modelling strategies by focusing on attackers, assets, and software and addresses the challenges in managing cyber risks in FinTech. The authors discuss detailed cybersecurity policies and strategies that can be used to secure financial institutions and provide recommendations to secure financial institutions from cyber-attacks.
Download or read book Artificial Intelligence in Finance written by Nydia Remolina and published by Edward Elgar Publishing. This book was released on 2023-01-20 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive analysis of the primary challenges, opportunities and regulatory developments associated with the use of artificial intelligence (AI) in the financial sector. It will show that, while AI has the potential to promote a more inclusive and competitive financial system, the increasing use of AI may bring certain risks and regulatory challenges that need to be addressed by regulators and policymakers.
