Source: Four Twenty Seven
The analyst may flag this site as one to examine more thoroughly during the due diligence process to understand what drives this facility’s exposure. This asset’s flood risk shows that it experiences relatively frequent flooding and is likely to experience more severe flooding moving forward. Analysts can use their understanding of the activities of the asset underlying a potential loan, alongside their information on the lifetime of the loan, to guide their interpretation of the climate risk assessment. For example, logistics facilities often rely on industrial equipment which can incur costly damage during flood events, and operations relying on specific equipment and facilities can be easily disrupted due to inundation. Likewise, this facility also relies on regional transportation infrastructure to receive and distribute goods.
Thus, flooding may be particularly significant for this facility since it is likely to experience disruptions if regional infrastructure is inundated even when its own equipment may not be damaged. This data highlights the importance of flood preparedness at this asset, as well as the preparedness of regional transportation infrastructure to withstand increasing extreme precipitation. The analyst may also note the asset’s high exposure to heat stress and water stress, since these are applicable due to the energy-intensive nature of freight logistics facilities and their reliance on outdoor labor. After exploring the underlying risk drivers at the asset, the credit analyst can discuss this risk with the loan applicant to understand if and how the applicant is preparing for these impacts and reducing the risk. Analysts’ well-rounded understanding of how an asset is exposed to changing conditions in the next several decades can inform their client engagement around risk and resilience, so they can build a thorough view on how this risk exposure may translate into credit impacts.
An Approach to Measuring Physical Climate Risk in Bank Loan Portfolios
7 Limitations and need for further research
Four Twenty Seven’s climate risk scoring methodology is based on the specific location of assets, which provides the projection of how assets may be affected by changing climate hazards. However, banks do not currently have complete records of the exact locations underlying their loans. This data gap makes it challenging for some banks to leverage this category of data12.
The primary output of this physical climate risk assessment is forward-looking exposure to several physical climate hazards out to mid-century, accounting for the sensitivity of different asset types. However, the impact of climate hazards on an entity’s credit worthiness depends not only on exposure and sensitivity, but also on preparedness. For example, a home that is elevated or an office that has elevated its electronics and put tiled floor on the ground floor, are less likely to incur costly flood damages than a home that sits on the ground in the floodplain and the office without flood defense. Preparedness is a key aspect for credit analysts to investigate if they find an asset has high exposure to climate risk.
An asset’s preparedness will depend both on its own structural resilience to extreme events, as well as the resilience of the surrounding region which it depends upon for resources and employees or clients (Ambrosio & Kim, 2019). This information is highly specific to the characteristics of each asset, but is an essential element in forming a comprehensive understanding of the potential material impacts of climate change on an asset or the organization that it is part of. There is a need for continued research around systematic, context-specific approaches to assessing resilience at scale. In the meantime, credit analysts can improve their understanding of their clients’ risks by leveraging the findings from physical climate risk assessments to engage with clients or potential clients about the exposure of their assets, asking specific questions about an asset’s operations, supply chain dependencies, resource use, market positioning, and other elements that will influence how likely a loan is to be impacted by the exposure of its underlying asset.
Four Twenty Seven currently provides an assessment of physical exposure, and is working with its parent company, Moody’s Corporation, to provide a quantitative estimate of the financial value at risk for each asset class.
Because banks have not traditionally consistently integrated climate risk into their credit evaluation processes, it is challenging to systemically project potential impacts in monetary terms. However, as described above, performing systematic climate risk screening is the first step from which to build a more sophisticated understanding of credit risk exposure and develop new financial metrics that connect financial risk to climate risk. As banks begin to integrate climate risk data more systematically into their processes, they have an opportunity to translate this information into indicators that speak to traditional financial reporting, such as Probability of Default and Loss Given Default.
Likewise, location-specific climate data can be used to develop scenario analysis, that considers the uncertainty of modeling the future. By leveraging science-driven data that shows different potential outcomes based on different climate futures, banks can develop approaches to understand the range of their risk under different scenarios. This can help informed a more nuanced view of loans’ risk exposure and also support growing reporting requirements. Four Twenty Seven recommends an approach to scenario analysis that accounts
12 GeoAsset. Spatial Finance Initiative. https://spatialfinanceinitiative.com/geoasset-project/
for the variations in projected physical impacts due to scientific uncertainty (Steinberg et al., 2019).
After obtaining forward-looking, location-specific projections that capture the potential impacts from a changing climate, banks also need capacity building to help analysts understand these impacts and respond accordingly. While it is essential to start with scientifically grounded, forward-looking data, the users of this data need to be trained to understand what potential impacts can mean for credit risk. As mentioned above, each climate hazard can affect corporate facilities, real estate and infrastructure assets, by increasing operating or repair costs and decreasing revenue due to business disruptions. These impacts can reduce funding reserves or lead to below-target revenues, with implications for loan repayment. Credit analysts need to understand these risk pathways so they can make informed decisions based on climate risk data. They also need to understand the uncertainty inherent in climate projections, the ways in which impacts vary in different regions and sectors, and the ways climate risks interact with other credit factors.
An Approach to Measuring Physical Climate Risk in Bank Loan Portfolios
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