LightBox and First Street Foundation Partner to Provide A New Model for Flood Data
As part of the partnership, LightBox is providing property and location data for more than 145 million U.S. properties via SmartParcels, the most complete parcel database in North America.
LightBox, First Street Foundation partner to provide a new model for flood data
LightBox, a leading provider of CRE data and workflow solutions, and First Street Foundation, a nonprofit 501(c)(3) research and technology group, have created a platform to provide new data and analytic capabilities to support investors, owners, brokers, lenders and others in assessing the impact of flood risk on individual properties and across large portfolios. The partnership provides:
- The first predictive, probabilistic model to estimate the impact of climate change on flooding down to the individual property level.
- Deeper data and analytics for property owners, investors, appraisers, lenders, and insurance companies to better understand and mitigate risk
- CRE practitioners the ability to examine portfolios and individual properties for flood risk, which could significantly impact property valuation and, ultimately, pricing.
- Important risk management tools for the CRE industry — which had more than $565 billion in US transaction activity in both 2018 and 2019, according to CBRE. Additionally, REITS and institutional owners combined, own and manage more than $3.23 trillion in US commercial real estate.
As part of the partnership, LightBox is providing property and location data for more than 145 million U.S. properties via SmartParcels, the most complete parcel database in North America. First Street will provide its climate-adjusted, predictive flood data and statistics based on future potential climate states as projected by the Intergovernmental Panel on Climate Change.
“Providing access to transformative data sets like these from First Street is critical to our mission at LightBox,” says Eric Frank, CEO of LightBox. “By including forward-looking, parcel-level data in our platform, we are enabling commercial owners, investors, lenders, and other real estate professionals to make successful decisions as they are better able to anticipate, quantify, and appropriately plan for risk and its mitigation throughout the real estate lifecycle.”
Available from LightBox, estimates and related data from the First Street Foundation Flood Model are integrated into the LightBox desktop SaaS applications, through its API and via bulk delivery.
The First Street Foundation Flood Model incorporates scientific data-driven predictions on how certain climate factors—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. Also, it considers parcel-specific nuance including the position of the building footprint and the topography of the property.
Based on this information, the First Street Foundation Flood Model produces probabilistic inundation statistics, in five-year intervals, from 2020 to 2050. The estimated risk for properties 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 partnership with LightBox creates the critical convergence of our scientific, data-driven model with location intelligence allowing us to make a range of reasonable, evidence-based conclusions on how a given area, down to the specific property parcel, may be impacted by flooding-related conditions,” adds Matthew Eby, Founder and Executive Director of First Street Foundation. “The conclusions that can be drawn will be meaningful and truly impactful for the real estate industry.”
Through its “Flood Lab”, First Street is also providing these data to a group of over 90 leading researchers from 20 of the country’s top academic institutions, to analyze and quantify the impacts of flooding on the national economy.
“Commercial real estate owners, investors, and the team involved in the research and due diligence process want data and information that will tell them whether flood-related events pose an investment threat, and whether returns adequately compensate for flood-related risk,” says Jacob Sagi, Professor of Finance and Wood Center in Real Estate Distinguished Scholar, University of North Carolina. “This information, when evaluated by the people who use best practices to interpret its impact, will inform prudent investment and underwriting decisions.”
Flood protection information (adaptation features) and flood statistics will be updated by First Street Foundation quarterly with a more comprehensive model and feature update annually. This new approach builds on the industry-standard maintained by FEMA and provides a timely and more extensive array of mapping and flood-related data to support real estate professionals as they evaluate and seek to mitigate property risk.