Quantifying the Effect of Climate on Corporate Credit Risk
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As climate risk is becoming an increasingly important part of credit risk management, we’re focused on enhancing our models with new data and analytics to help customers manage their portfolios with better accuracy.
Moody’s Analytics award-winning Expected Default Frequency (EDF™) model has been adjusted to quantify the impact of climate on credit risk via firm earnings and valuations. In this 90-minute webinar, we’ll provide a deep dive, quantitative overview of the methodology for our Climate-Adjusted EDF model:
• Impacts of climate on corporate credit risk and what climate scenarios tell us
• Leveraging Moody’s ESG firm-level physical risk scores for treatment of physical risk in the Climate-Adjusted EDF model
• Quantifying the impact of transition to firm-level risk metrics using firm financials and scope 1 and 2 emissions
• Discussion on how the Climate-Adjusted EDF model can be put into action to help you uncover risks sooner for private and public companies
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SpeakersMateusz Giezek Director Moody's Analytics
Nils Grevenbrock Associate Director - Research Moody's Analytics
Petr Zemcik Senior Director - Research Moody's Analytics
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Dr. Petr Zemcik is a Senior Director at the Moody’s Analytics London office who supervises a focused applied research team of risk modelers and data scientists located in the UK, the US, Czechia, and UAE. Petr leverages on his extensive experience as an engagement lead for internal and external projects to design and validate retail and corporate PD/LGD/EAD credit risk models for IFRS 9, A-IRB, and stress testing, as well as macroeconomic country and regional models for economic forecasting. His team currently concentrates on linking climate change scenarios to credit risk and on embedding macroeconomic scenarios across credit risk models, while also working on projects and products related to regulatory compliance for stress testing & ICAAP and CECL & IFRS 9. The team con tributes to the support of the following Moody’s credit risk products and models: Corporate Expected Default Frequency (EDF) for Risk Calc and Credit Edge; Credit Transition Model (CTM) & Moody’s Market Implied Ratings (MIR); and PD/Prepayment/LGD/EAD for retail portfolios in the Portfolio Analyzer (PA) platform. Petr previously worked at CERGE-EI, a joint workplace of the Center for Economic Research and Graduate Education of Charles University in Prague and the Economics Institute of the Academy of Sciences of the Czech Republic, and at Southern Illinois University in Carbondale. He holds a PhD and an MA in Economics from the University of Pittsburgh and an MSc in Econometrics and Operations Research from the University of Economics in Prague.