Cristian deRitis, Deputy Chief Economist at Moody’s Analytics, specializes in assessing the economy’s impact on household finance, housing, credit markets and public policy. Named on two U.S. patents for credit modeling, he created loss forecasting and stress testing systems for financial institutions. He joined Moody’s in 2008, after serving as a director with Fannie Mae. He also was an adjunct professor of economics at Johns Hopkins University..
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Loss Accounting: CECL: New credit loss accounting standard that replaces the current ALLL accounting standard.
Stress Testing: US: Examination of the possible impact of an adverse scenario on a firm and/or industry.
Cris deRitis, Chief Deputy Economist with Moody's Analytics discusses the current and anticipated trends in U.S. economic and household credit conditions.
How should we prepare for the next recession?
Learn to differentiate C&I, CRE, retail, and securities. Choose approaches at the right level of flexibility and sophistication. Apply model-free solutions based on historical internal or industry data.
Having achieved the longest expansion in history, what's next for the US economy? We will identify current downside – and upside – risks that could pull the economy into recession or propel it forward. We identify short, medium, and long-term risk factors and introduce a methodology for incorporating these risks into a globally consistent framework. While no model can forecast the future with certainty, scenarios with mathematically derived probability weights can manage these risks and lead to better, faster decisions.
Climate change and its increasing economic toll on businesses in different sectors of the economy is discussed, including how to operationalize the response to climate change risk, given stakeholder need. Also discussed is the linkage between environmental risk and other ESG risk factors to security returns and measures of credit risk.
With many of the larger SEC filers well ahead in their CECL preparations and gearing up for validation, we examine how the requirements of an R&S forecast and reversion may be interpreted.