IMF Developing new Tools to identify Financial Trouble Spots

• Author: Marina Moretti
• Position: IMF Monetary and Capital Markets Department
• Pages: 26

Page 26

The IMF is developing new applications for stress tests and other quantitative risk-assessment models to help identify financial system vulnerabilities in member countries, in the wake of the U.S. subprime crisis.

The recent turmoil in credit markets is a clear reminder that financial globalization brings not only benefits-the deepening of financial markets and internationalization in capital allocation- but also new risks and challenges for policymakers. Globalization links national economies in a vast network of closely interconnected on-and off-balance-sheet positions, creating the potential for financial instability to be transmitted from one country to other countries or to affect regional and global markets.

A range of analytical tools being developed by the IMF's Monetary and Capital Markets Department (MCM) will be able to better account for the complex linkages between the global economy and modern financial markets and thereby help sharpen the IMF's monitoring of member countries' financial systems.

Complex models for complex realities

Specific areas of the IMF's work include further developing credit risk analysis; focusing more on "second-round effects" of shocks- both interactions within the financial sector and feedback between the financial sector and the macroeconomy; and expanding existing approaches to liquidity risk modeling.

* Credit risk modeling. Work in this area revolves around three broader methodologies, each of which can be applied either at an aggregated level (a group of banks) or at the bank-by-bank level, and each of which has already been used for stress testing or scenario analysis in a number of countries.

For example, one application models portfolio credit risk based on CreditRisk+, a tool that is already being used by financial institutions and supervisors to compute the credit portfolio loss distribution-that is, the probability of losses on a given credit portfolio. This application can be useful for scenario stress testing when complemented with models of the probability of default (the likelihood that a credit will not be repaid) and loss given default (the fraction of the credit that will not be recovered in the event of default).

Another relatively new direction of work is macro stress testing under data constraints, an approach that allows the impact of macroeconomic shocks on banks' economic capital in the presence of short time series of...