Since the global financial crisis, bank stress testing has become an essential part of regulators’ toolkits for monitoring and maintaining financial stability. Anticipating the results of a formal stress test through simulation can enhance a bank's internal risk management as well as provide strategic business insight.
In this webinar, you will learn:
Methods for stressing default probabilities on particular macroeconomic scenarios.
How to implement stressed PDs in a portfolio simulation methodology to calculate scenario specific expected loan loss rates.
Insight from two simulation case studies for corporate loan portfolios: (1) The Federal Reserve’s CCAR/DFAST stress tests, and (2) a stress test for the five largest banks in Australia approximating the Australian Prudential Regulation Authority’s (APRA) stress test.
How to implement simulation analysis as an efficient repeatable and reduced computational costs process.
Moody's Analytics Early Warning System helps streamline the portfolio management process. It empowers users to make better, faster credit decisions with a new suite of metrics, tools, and analytics.
A new study from Moody's Analytics uses a quantitative Expected Default Frequency (EDF) model to assess the impact of the pandemic on corporate credit risk in Southeast Asia.
China’s corporate credit market has grown rapidly in recent years as both a cause and effect of its growing economy.
In this webinar Moody’s Analytics discuss the Marco-economic and credit market conditions likely to affect the future risk of default for Chinese companies; way to measure and manage the default risk of Chinese firms, and strategies for early detection of default risk.
This whitepaper discusses the findings of our simulation exercise to the corporate loan portfolios of Australia's five largest banks.
In this webinar, David Hamilton presents the results of a simulated stress test of the corporate loan portfolios of Australia’s five largest banks (by asset size) conducted by Moody’s Analytics.
In this webinar, Moody’s Analytics combines the techniques of network analysis with the richness of Moody’s CreditEdge™ platform to compute systemic risk measures spanning the last 20 years for five major southeast Asian economies.
This article looks back at the Asian financial crisis of 1997-1998 and applies new methods of measuring systemic risk and pinpointing weaknesses, which can be used by today’s financial institutions and regulators.
Identifying At-Risk Names in Your Credit Portfolio
Through much of its history Best Buy was considered one of the most successful retail stores in the US. However, since 2010 the electronics retailer has faced business and financial challenges that are placing increasing pressure on its credit quality.