With growing attention on the impacts of climate change, investors and other commercial real estate stakeholders are paying more attention to rising sea levels and flood risk than ever before. Yet the traditional approach to assessing a property’s exposure to flood risk is inadequate. The promising news is that flood risk modeling is becoming more sophisticated, which gives commercial real estate lenders and investors tools for more accurate real estate decisions.
To kick off our LightBox Spotlight series, I posed a few questions to Zach Wade, Vice President, Data Science, to get his thoughts on how the tools for assessing property-level flood risk are evolving, why the new LightBox-First Street partnership is so timely, and how the commercial real estate sector is responding to our growing awareness of climate change risk.
What are the issues related to how flood risk is traditionally assessed at commercial problems?
Zach Wade: “Assessing flood risk has been a standard part of environmental due diligence, but the traditional approach of relying on FEMA maps to determine if the target property is located within the 100-year flood plain only scratches the surface. There are a number of limitations associated with this approach. First, FEMA maps are outdated in many areas, and the process of updating them, as we saw in the wake of Hurricane Sandy in New York and New Jersey, becomes very politicized. Second, FEMA maps don’t provide precise inundation estimates at the property boundary level. Third, FEMA maps are backward-looking. They do not consider climate change, for example by accounting for the likelihood of variables like rising sea levels and how these changes could increase a property’s vulnerability to flooding in the future. Fortunately, important advances are moving the needle toward more accurate ways of assessing property flood risk.”
Can you explain the new LightBox partnership with First Street and the market challenges it can help commercial real estate professionals face?
Wade: “The First Street Foundation Flood Model is the industry’s first predictive, probabilistic model to estimate the impact of climate change on flooding down to the individual property level. It incorporates scientific data-driven predictions on how certain climate factors (e.g., sea-level rise, changes in precipitation patterns, and ocean temperatures) influence future flooding, including hurricane storm surge, tidal flooding, pluvial (precipitation) flooding, and fluvial (riverine) flooding. Our collaboration with First Street allows for their modeling to be applied at the property level using LightBox data in a way that wouldn’t otherwise be possible. Notably, it also considers parcel-specific nuances, including the position of the building footprint and the topography of the property.
“The estimated risk is captured in a Flood Factor™ rating system that ranks on a scale from 1 (minimal) to 10 (extreme), the risk associated with a specific property. This quantitative output can be used by property owners, investors, appraisers, lenders, and insurance companies to better anticipate, quantify and appropriately plan for risk associated with flood-related events. The LightBox partnership with First Street Foundation gives us property-level data on the potential likelihood and severity of a given flood event. This, in turn, enables CRE decision-makers to think about the impact that flood risk could have on a particular property’s cash flow, physical property damage and even the potential for repricing if, for instance, a property hasn’t historically been in a flood zone but is later classified as being in one based on factors related to climate change.
“For example, the below image is a screenshot from the LightBox LandVision application that displays FEMA 100-yr flood zone (blue shading) alongside parcels (highlighted in yellow or green) with high Flood Factor™ scores. Notice that First Street is detecting properties with significant flood risk that actually fall outside of the FEMA boundary.”
Question: What other types of climate change-related data is LightBox watching?
Wade: “In addition to flood risk, climate change risk includes a number of other types of risk like wind, wildfire, drought and heat. One interesting thing I’m working on now is a source for detecting and tracking wildfire events in real-time, which would enable our customers to be informed about imminent threats more rapidly than ever before. We’re also working to translate climate risk forecasts to actual property-level economic impact, to so our customers don’t need to be experts in climate science to understand the potential impact on commercial real estate. For example, LightBox maintains research partnerships with academia, such as one with the University of North Carolina to quantify the financial risk associated with flooding and understand whether or not mortgage pricing accurately reflects flood risk for commercial properties.”
Question: Are you seeing commercial real estate investors and lenders changing their behavior to consider climate change risk as a factor in their decision making?
Wade: “As the science advances and awareness grows, I expect to see proactive investors and lenders considering climate change risk more and more. For instance, lenders are starting to look more holistically at their commercial property loans to gauge the portfolio risk they may face if the majority of their loans are located in flood-prone areas like Houston and Miami. As environmental and climate issues become more important, major investors will also be pressured to pay attention to climate change not just to protect their own risk exposure but to manage reputational risk. Our focus on staying on top of the latest modeling advances allows us to meet the commercial real estate sector’s growing demand for more sophisticated tools to accurately assess climate risk exposure at the property level.”
About ZACH WADE
Zach is Vice President, Data Science at LightBox where he is responsible for creating new services that leverage structured and unstructured data, remote sensing, and machine learning to help enable the most successful decisions in real estate. He holds an MSc. in Economics & Management from the London School of Economics, with Distinction and the Award for Best Dissertation. Zach has held numerous quantitative research positions, including at the Paul Milstein Center for Real Estate at Columbia University where he contributed to financial economics research on the mortgage crisis of 2008; Deutsche Asset & Wealth Management (now DWS) where he focused on global quantitative research for commercial real estate, infrastructure, and commodities securities, and real assets; BuildFax where he led data science and created new products from building permit data for the investment and insurance industries; and a CRE data startup he co-founded as head of data science.
FOR MORE INFORMATION
Along with leading experts from academia, mortgage lending and property due diligence who tackled why the real estate finance world has largely ignored the impact of increased flood risk, Zach Wade outlined the limitations of traditional approaches, and the innovative risk management tools available to proactively address flood in today’s underwriting as rising sea levels become a very real concern for commercial and residential properties in flood-prone zones.
Category Commercial Real Estate