Rossi, professor of the practice in finance at the University of Maryland’s Robert H. Smith School of Business, has been studying those risks. This week, he will present his findings in a meeting of the Federal Housing Finance Agency.
He will be recommending that the agency integrate climate risk management governance and processes into its existing enterprise risk management work. He says the agency should determine how much credit risk exposure is associated with specific types of natural disasters and climate-related events. He recommends conducting analytics to quantify the direct impact of natural disaster and climate-related events on key risk types. For example, he says, how hurricanes impact mortgage default risk.
“One of the most difficult aspects for financial institutions in conducting climate change risk analysis is integrating physical climate event data with financial and risk information,” Rossi says.
Rossi is an expert in risk, and spent 25 years in banking and in government before coming to academia. In the financial crisis of 2008-2009, he was chief risk officer for Citigroup's Consumer Lending Division, overseeing the risk of the bank’s $300-billion secured consumer asset portfolio.
His presentation before the FHFA will demonstrate how to directly link climate events to mortgage risk, using a statistical modelling technique.
Rossi recently completed an empirical study on the impact of hurricane frequency and intensity on mortgage default risk. He says the percentage increase in hurricane intensity and frequency scenarios aligned with NOAA long-range hurricane forecasts and were used to quantify a forward-looking assessment of the incremental effect of hurricane risk on mortgage default.
In his research, which included a sample of 100,000 Freddie Mac mortgages along with FEMA data, he finds that with an increasing frequency of major hurricanes there will also be a sizable increase in borrower defaults. The results, he writes, carry “significant implications” for borrowers and investors in mortgage credit risk.
This type of analysis could be expanded, he says, across other severe weather events and natural disasters, and financial and nonfinancial risks, to measure mortgage loss severity and uncover risk.
By doing so, Rossi says, policymakers could simulate potential loss outcomes and help prepare government sponsored enterprises.
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