Tony Hughes leads Moody’s Analytics Research and oversees credit analysis consulting projects for global lending institutions. An expert in applied econometrics, he helped create stress testing and loss forecasting approaches for retail, C&I and commercial real estate portfolios. Tony developed a methodology for stress-testing bank deposit books and is working on approaches to streamline economic scenario building and improve economic path simulation.
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.
We look at climate risk and consider how a heating planet might impact a bank's performance
With ever-expanding and improving AI and Machine Learning available, we explore how a lending officer can make good decisions faster and cheaper through AI. Will AI/ML refine existing processes? Or lead to completely new approaches? Or Both? What is the promise? And what is the risk?
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.