Stress Testing Used-Car Prices
In this presentation we presented a quantitative methodology for incorporating economic factors into car price forecasts.
In this presentation we presented a quantitative methodology for incorporating economic factors into car price forecasts.
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We look at climate risk and consider how a heating planet might impact a bank's performance
Expanding Roles of Artificial Intelligence and Machine Learning in Lending and Credit Risk Management
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?
Conservative Banks Do Not Need Conservative Models
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?
Model Validation Need Not Be a Blood Sport
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.
Will CECL Ultimately Be Worth All the Fuss?
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 Real Value of Stress Testing: Has CCAR Been Validated?
The theory that banks are now safer because of CCAR, though, has not yet been tested.
CECL, IFRS 9 and the Demand for Forecast Stability
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.
Climate Change Stress Testing
As evidence of climate change builds and threats materialize,data will be invaluable in creating a framework for making future credit decisions.
Human Versus Machine: The Pros and Cons of AI in Credit
In recent years, attention has increasingly turned to the promise of artificial intelligence (AI) to further increase credit availability and to improve the profitability of banks and other lenders. But what is AI?
Finding a CECL Solution for Smaller Banks
Good-quality CECL projections can be developed using high-quality data that is available free of charge.