Credit Risk And Credit Access In Asia

This conference proceedings discusses progress made since the 1997-98 financial crisis and presents summaries of the situation in each country.

This publication is based on the proceedings of the 4th meeting within the framework of the Forum for Asian Insolvency Reform, organised by the OECD, the World Bank and the Asian Development Bank and held in New Delhi, India, held in November 2004. It contains individual country reports on key trends and developments relating to debt, insolvency and credit risk management issues since the 1997-1998 Asian financial crisis; as well as four papers which explore the issues from a regional perspective.

There is limited access for small and medium-sized enterprises (SMEs) to bank credit. This book proposes new and sustainable models to help ease the access of SMEs to finance and boost economic growth and job creation in Asia. This book looks at the difficulties of SMEs in accessing finance and suggests ways on how to mitigate these challenges. It suggests how we can develop credit information infrastructures for SMEs to remedy the asymmetric information problem and to utilize credit rating techniques for the development of a sustainable credit guarantee scheme. The book provides illustrations of various Asian economies that implemented credit guarantee schemes and credit risk databases and is a useful reference for lessons and policy recommendations.

This book records the first success stories of a new form of financial intermediation, the hometown investment fund, that has become a national strategy in Japan, partly to meet the need to finance small and medium-sized enterprises (SMEs) after the devastating earthquake and tsunami in March 2011. The hometown investment fund has three main advantages. First, it contributes to financial market stability by lowering information asymmetry. Individual households and firms have direct access to information about the borrowing firms, mainly SMEs, that they lend to. Second, it is a stable source of risk capital. The fund is project driven. Firms and households decide to invest by getting to know the borrowers and their projects. In this way the fund distributes risk but not so that it renders risk intractable, which was the problem with the “originate and distribute” model. Third, it contributes to economic recovery by connecting firms and households with SMEs that are worthy of their support. It also creates employment opportunities, at the SMEs as well as for the pool of retirees from financial institutions who can help assess the projects. Introduction of the hometown investment fund has huge global implications. The world is seeking a method of financial intermediation that minimizes information asymmetry, distributes risk without making it opaque, and contributes to economic recovery. Funds similar to Japan’s hometown investment fund can succeed in all three ways. After all, the majority of the world’s businesses are SMEs. The first chapter explains the theory behind this method, and the following chapters relate success stories from Japan and other parts of Asia. This book should encourage policymakers, economists, lenders, and borrowers, especially in developing countries, to adopt this new form of financial intermediation, thus contributing to global economic stability.

In this paper, we provide an overview of the concerns surrounding the variations in the calculation of risk-weighted assets (RWAs) across banks and jurisdictions and how this might undermine the Basel III capital adequacy framework. We discuss the key drivers behind the differences in these calculations, drawing upon a sample of systemically important banks from Europe, North America, and Asia Pacific. We then discuss a range of policy options that could be explored to fix the actual and perceived problems with RWAs, and improve the use of risk-sensitive capital ratios.

In 2011 the World Bank—with funding from the Bill and Melinda Gates Foundation—launched the Global Findex database, the world's most comprehensive data set on how adults save, borrow, make payments, and manage risk. Drawing on survey data collected in collaboration with Gallup, Inc., the Global Findex database covers more than 140 economies around the world. The initial survey round was followed by a second one in 2014 and by a third in 2017. Compiled using nationally representative surveys of more than 150,000 adults age 15 and above in over 140 economies, The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution includes updated indicators on access to and use of formal and informal financial services. It has additional data on the use of financial technology (or fintech), including the use of mobile phones and the Internet to conduct financial transactions. The data reveal opportunities to expand access to financial services among people who do not have an account—the unbanked—as well as to promote greater use of digital financial services among those who do have an account. The Global Findex database has become a mainstay of global efforts to promote financial inclusion. In addition to being widely cited by scholars and development practitioners, Global Findex data are used to track progress toward the World Bank goal of Universal Financial Access by 2020 and the United Nations Sustainable Development Goals. The database, the full text of the report, and the underlying country-level data for all figures—along with the questionnaire, the survey methodology, and other relevant materials—are available at www.worldbank.org/globalfindex.

The long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics. SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models. Understand the general concepts of credit risk management Validate and stress-test existing models Access working examples based on both real and simulated data Learn useful code for implementing and validating models in SAS Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. Credit Risk Analytics is the reference every risk manager needs to streamline the modeling process.