Tony was formerly the lead Asia-Pacific economist for Moody’s Analytics. Prior to that, he held academic positions at the University of Adelaide, the University of New South Wales, and Vanderbilt University. He received his PhD in Econometrics from Monash University in Melbourne, Australia. Recent Articles:
Human Versus Machine: The Pros and Cons of AI in Credit
Commercial Lending Imbalances and the Looming Recession
Credit Risk Advisory Services: Moody's Analytics credit risk advisory services enable faster, better informed credit decisions through a holistic and consistent assessment of risk.
Credit Risk Modeling: Moody’s Analytics delivers award-winning credit models and expert advisory services to provide you with best-in-class credit risk modeling solutions.
Economic Forecasts: Moody's Analytics provides trusted macro and regional forecasts to help clients assess potential economic outcomes.
Systemic Risk: Moody's Analytics provides comprehensive measures of network connectivity in the financial services industry.
Stress Testing: Moody’s Analytics helps financial institutions develop collaborative, auditable, repeatable, and transparent stress testing programs to meet regulatory demands.
Portfolio Optimization: Quantify diversification benefits across portfolios and define risk types that inform risk management and active asset allocation decisions.
Economic Advisory: Moody's Analytics provides expert economic advisory services to clients to minimize risks and maximize opportunities.
When banks manage risk, conservatism is a virtue. We, as citizens, want banks to hold slightly more capital than strictly necessary and to make, at the margin, more provisions for potential loan losses. Moreover, we want them to be generally cautious in their underwriting. But what is the best way to arrive at these conservative calculations?
The traditional build-and-validate modeling approach is expensive and taxing. A more positive and productive validation experience entails competing models developed by independent teams.
The industry is currently a hive of CECL-related activity. Many banks are busily testing their systems or finalizing their preparations for the go-live date, which is either in January 2020 or somewhat later, depending on the organization. Some are still making plans for implementation, and the rest are worried that they should be.
The theory that banks are now safer because of CCAR, though, has not yet been tested.
Loan-loss provisioning models must take a variety of economic and client factors into account, but, with the right approach, banks can develop sensible loss forecasts that are more accurate and less susceptible to volatility.
As evidence of climate change builds and threats materialize,data will be invaluable in creating a framework for making future credit decisions.