Abstract
IntroductionLong-run Macro-Prudential stability objectives for the banking system have recently motivated a detailed focus on potential future credit risks stemming from climate change. Led by regulators and the NGFS, early approaches apply smooth, top-down scenarios that utilize carbon emissions data combined with physical risk metrics. This general climate stress test approach assesses future credit losses for individual firms and the banking system. While the NGFS approach is in its infancy, a number of discussion points have been raised related to how the approach assesses future credit risks. In contrast to the NGFS approach that focuses on changes to long-run economic growth trends, higher credit risks generally arise from unexpected economic shocks to cashflows and asset values. Systematic shocks that impact many firms like those observed during the last three economic recessions clearly produce higher volatility and systematic deviations from average economic trends.MethodsIn this paper we briefly review aspects of current climate stress test approaches to set the context for our primary focus on assessing future climate induced credit risk and credit risk volatility using a multi credit-factor portfolio framework applied to a benchmark US C&I credit portfolio. First we compare various NGFS climate scenarios using NGFS GDP measures to a CCAR severely adverse stress scenario. We then undertake two additional assessments of future climate driven credit risk by applying an assumed relationship between NGFS global mean temperatures (GMTs) and credit-factor volatilities. All three prospective climate credit risk assessments utilize an empirically-based, credit-factor model estimated from market-based measures of credit risk to highlight the potential role for climate induced increases in volatility. The potential future drivers of volatility could stem from narrower physical risks or broader macro-economic, social or other systematic shocks driven by climate change. All three predicted credit loss assessments suggest that volatility not changes to economic trends ultimately drives higher potential credit risks relating to climate change.ContributionsThe key contributions of this paper are the application of empirically based credit factor models combined with higher climate-driven volatility assumptions that support statistical assessment of how climate change could impact credit risk losses.
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