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Banking Regulation: Enhanced Guidance on Commercial Real Estate Risks Needed
This book presents the results of a study of FDIC-supervised institutions with significant acquisition, development, and construction (ADC) loan concentrations that did not fail during the recent economic downturn. ADC loans are considered the riskiest type of commercial real estate (CRE) lending. During the recent financial crisis, FDIC analysis shows that failed institutions had concentrations of ADC loans to total assets that were roughly three times the average of concentrations of non-failed institutions. This book studies the characteristics and supervisory approaches for FDIC-supervised institutions that had significant ADC loan concentrations and were not considered to be problem banks as of April 2011, with a focus on the identifying factors that may have helped banks mitigate the risks historically associated with ADC concentrations during periods of economic stress.
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.
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.
The evolution of risk management has resulted from the interplay of financial crises, risk management practices, and regulatory actions. In the 1970s, research lay the intellectual foundations for the risk management practices that were systematically implemented in the 1980s as bond trading revolutionized Wall Street. Quants developed dynamic hedging, Value-at-Risk, and credit risk models based on the insights of financial economics. In parallel, the Basel I framework created a level playing field among banks across countries. Following the 1987 stock market crash, the near failure of Salomon Brothers, and the failure of Drexel Burnham Lambert, in 1996 the Basel Committee on Banking Supervision published the Market Risk Amendment to the Basel I Capital Accord; the amendment went into effect in 1998. It led to a migration of bank risk management practices toward market risk regulations. The framework was further developed in the Basel II Accord, which, however, from the very beginning, was labeled as being procyclical due to the reliance of capital requirements on contemporaneous volatility estimates. Indeed, the failure to measure and manage risk adequately can be viewed as a key contributor to the 2008 global financial crisis. Subsequent innovations in risk management practices have been dominated by regulatory innovations, including capital and liquidity stress testing, macroprudential surcharges, resolution regimes, and countercyclical capital requirements.