{"id":605262,"date":"2023-08-01T05:52:20","date_gmt":"2023-08-01T12:52:20","guid":{"rendered":"https:\/\/www.esri.com\/about\/newsroom\/?post_type=wherenext&p=605262"},"modified":"2025-01-15T09:55:10","modified_gmt":"2025-01-15T17:55:10","slug":"mary-lennon-fannie-mae-profile","status":"publish","type":"wherenext","link":"https:\/\/www.esri.com\/about\/newsroom\/publications\/wherenext\/mary-lennon-fannie-mae-profile","title":{"rendered":"How Fannie Mae Studies Climate Impact on US Housing"},"author":501,"featured_media":0,"parent":0,"menu_order":0,"template":"","format":"standard","meta":{"_acf_changed":false,"sync_status":"","episode_type":"","audio_file":"","castos_file_data":"","podmotor_file_id":"","cover_image":"","cover_image_id":"","duration":"","filesize":"","filesize_raw":"","date_recorded":"","explicit":"","block":"","itunes_episode_number":"","itunes_title":"","itunes_season_number":"","itunes_episode_type":"","_links_to":"","_links_to_target":""},"categories":[],"tags":[26512,278902,281,1461,486642],"department":[476782,488822],"wherenext-category":[],"industry":[],"class_list":["post-605262","wherenext","type-wherenext","status-publish","format-standard","hentry","tag-climate-change","tag-data-science","tag-location-intelligence","tag-sustainability","tag-wherenext-profiles","department-new-analyst","department-sustainability-risk"],"acf":{"short_description":"Climate impact adviser Mary Lennon and team are using a geographic approach to analyze and mitigate the effects of natural hazards on US housing.","pdf":{"host_remotely":false,"file":"","file_url":""},"flexible_content":[{"acf_fc_layout":"content","content":"Data science was about the furthest thing from Mary Lennon\u2019s mind in college. A double-major in anthropology and art history at Temple University, she dreamed of becoming an archaeologist."},{"acf_fc_layout":"sidebar","layout":"standard","image_reference":null,"image_reference_figure":"","spotlight_image":null,"section_title":"","spotlight_name":"","position":"Left","content":"Article snapshot:<\/strong> To assess housing risks from climate change, Mary Lennon and her Fannie Mae colleagues use predictive models to process national datasets and reveal hyperlocal realities.","snippet":""},{"acf_fc_layout":"content","content":"Her research stoked a fascination with maps and what they could reveal about social change. Eventually, that set her on a journey to becoming a geographic data scientist<\/a>. Through a career that\u2019s spanned commercial archaeology, retail analytics, and climate science, Lennon has helped organizations mitigate risk and discover opportunities by using geographic information system<\/a> (GIS) technology to extract insights from huge datasets.\r\n\r\nToday, as a climate impact adviser at mortgage financer Fannie Mae, she uses spatial context to understand how climate change<\/a> impacts homeowners and the business of real estate. With location intelligence gleaned from GIS, Lennon assesses current and future natural-hazard risks to US homeowners and Fannie Mae, which, as of December 31, 2022, backed over 25 percent of US single-family mortgage debt.\r\n

The Fannie Mae Team Examining the Future of Housing <\/strong><\/h3>\r\nLike many Fortune 500 organizations<\/a> today, Fannie Mae faces the challenge of adapting to climate change. Using a geographic approach<\/a>, Lennon and the analytics and modeling team examine how factors like flood zones, demographic trends, borrower performance, and property values can interact to determine the fate of neighborhoods facing extreme weather.\r\n\r\n\u201cGIS is fundamental to climate risk,\u201d Lennon explains. \u201cKnowing exactly where a property is and understanding the surrounding environment is absolutely required for understanding climate risk, especially when you think of something like floods.\u201d"},{"acf_fc_layout":"content","content":"A new study in Nature Climate Change<\/a> found that outdated flood maps, insufficient insurance policies, and buyers unaware of natural hazard risks are leading the real estate market to dangerously underestimate the threat of climate change<\/a>. Fannie Mae\u2014which was created by the US government after the Great Depression to help ensure access to affordable mortgage funds across America\u2014is prioritizing predictive climate intelligence to educate homeowners and avoid losses in home value.\r\n

Climate Analysis That Puts People First<\/strong><\/h3>\r\nLennon and her colleagues contribute to Fannie Mae\u2019s mission of supporting homeowners and renters by helping homeowners and multifamily property owners prepare for future climate realities. The location insights produced by the team help guide the organization\u2019s push for updated building standards, stronger insurance policies, and increased homeowner awareness.\r\n\r\nFor instance, a property might sit outside a FEMA 100-year flood zone, meaning the homeowner is not required to get flood insurance. Yet the maps Lennon creates show that the house may be at risk. That can spur action, either at a governmental level or in the homeowner\u2019s own decisions<\/a>."},{"acf_fc_layout":"sidebar","layout":"standard","image_reference":null,"image_reference_figure":"","spotlight_image":null,"section_title":"","spotlight_name":"","position":"Right","content":"Climate Risk: Anticipating and Taming the Impacts<\/strong>\r\n\r\nTo gauge climate vulnerabilities, business executives are using location technology to model storm impacts<\/a>, and employing GIS-powered dashboards to plan their response. Homeowners are using tools like the Climate Mapping for Resilience and Adaptation<\/a> website.","snippet":""},{"acf_fc_layout":"content","content":"Because there is no silver bullet when it comes to predicting climate impacts, Lennon and her colleagues take multiple models into account. Maps are the central organizing point for huge national datasets on natural hazards and their impacts on Fannie Mae\u2019s portfolio of single-family loans on over 17 million properties. By using GIS to analyze massive troves of information, the team can understand risks to very small pieces of land\u2014down to studying how water viewsheds from individual houses can raise homeowners\u2019 awareness of flood risks.\r\n\r\n\u201cWe don\u2019t do climate analytics without a correlation to how it actually impacts people,\u201d says Tim Judge, senior vice president, head of modeling and chief climate officer at Fannie Mae, who works closely with Lennon. \u201cI don\u2019t talk about the property\u2014I talk about the people who are living in the property.\u201d\r\n\r\nTo account for the accelerating pace of climate change, Lennon and the team also examine models<\/a> that account for more recent meteorological trends. Combined with Fannie Mae\u2019s extensive property data and valuation estimation tools\u2014as well as demographic data that identifies potentially vulnerable populations\u2014those models reveal how climate trends could threaten homes in America over time.\r\n\r\n\u201cIt is a really complicated story to tell,\u201d Lennon says. \u201cShowing that on a map is probably the most natural way to do it.\u201d"},{"acf_fc_layout":"quote","image":605252,"text":"For certain perils, in terms of natural disasters and climate change, being very good and very specific about property location, particularly through mapping, is incredibly important.","author_name":"SVP, head of modeling and chief climate officer at Fannie Mae","author_profession_organization":"Tim Judge"},{"acf_fc_layout":"content","content":"

From Archaeology to Climate Science, a Career Driven by Geospatial Data<\/strong><\/h3>\r\nLennon first applied a geospatial lens to big datasets while working in cultural resource management at architecture and engineering firms John Milner Associates and AECOM.\r\n\r\nAt AECOM, Lennon was involved in creating predictive models that helped the company locate likely sites of archaeological importance across an entire state\u2014a key component of impact surveys for building projects. The work opened her eyes to the power of combining data science with spatial analysis<\/a>. \u201c\u2019This is the coolest thing I\u2019ve ever seen,\u2019\u201d she remembers thinking. \u201cIt was a great first exposure to GIS.\u201d\r\n\r\nDuring that period, Lennon balanced full-time work at AECOM with her education in GIS and data technology and night shifts as a waitress.\r\n\r\n\u201cI think anyone who has met her instantly recognizes she\u2019s absolutely bright, super focused, and driven,\u201d says Matt Harris, a mentor and supervisor of Lennon\u2019s at John Milner Associates and AECOM and now a University of Pennsylvania faculty member.\r\n\r\nLennon joined Fannie Mae in 2019, attracted by the prospect of working on datasets that encompassed the whole nation.\r\n\r\nWith the analysis she and her colleagues now provide, Fannie Mae is working to better understand not just general climate trends, but how particular impacts coincide with socioeconomic factors\u2014on a hyperlocal level.\r\n\r\n\u201cIn some vulnerable communities that have had historically less investment in infrastructure and the like, the impacts of climate are far greater,\u201d Judge says."},{"acf_fc_layout":"quote","image":605242,"text":"Every customer has big ESG plans, and spatial analytics is another one of those magic components that can bring a ton of insight into a field that still needs a lot of definition.","author_name":"University of Pennsylvania faculty","author_profession_organization":"Matt Harris"},{"acf_fc_layout":"content","content":"

Maps That Tell a Story\u2014And Make a Difference<\/strong><\/h3>\r\nLennon began her career learning from colleagues who were pushing the limits of programming languages and GIS technology. Today, she\u2019s a leader in her own right, overseeing Fannie Mae\u2019s GIS and fielding geospatial questions from coworkers.\r\n\r\nShe frequently presents to an internal climate action working group and briefs upper management."},{"acf_fc_layout":"sidebar","layout":"standard","image_reference":null,"image_reference_figure":"","spotlight_image":null,"section_title":"","spotlight_name":"","position":"Right","content":"Location Analysis Across Industries<\/strong>\r\n\r\nAs part of a master\u2019s dissertation at the University of Liverpool, Mary Lennon created propensity models for an e-commerce retailer, using geography to estimate the likelihood that shoppers would become repeat customers<\/a>. The company hired her for the remainder of her stay in England.","snippet":""},{"acf_fc_layout":"content","content":"\u201cWhen we first stood up the climate group, we didn\u2019t have nearly the amount of GIS expertise,\u201d Judge says. Once Lennon joined, \u201cit was a paradigm change in terms of what we could do and how we could tell stories,\u201d he says. \u201cIt also made us focus more on bringing an enterprise solution<\/a> to Fannie Mae for GIS and location intelligence overall.\u201d\r\n\r\nFor Lennon, storytelling can make all the difference. Climate impact maps that vividly show what the housing market might look like in 50 years and demonstrate the consequences of today\u2019s decisions have the power to shift thinking among stakeholders.\r\n\r\n\u201cWe think of mapping as a tool that can be used to share analyses, to share viewpoints, to effect change in a variety of different ways,\u201d Lennon says. \u201cAs we consider what kind of change we can effect and how we can do that responsibly, we have the information that we need at hand to help inform industry stakeholders.\u201d"}],"references":null},"yoast_head":"\nFannie Mae Uses Massive Datasets to Examine Local Housing Trends<\/title>\n<meta name=\"description\" content=\"With the mission to facilitate equitable and sustainable access to homeownership and quality affordable rental housing across America, Fannie Mae is using location-specific models to predict climate impacts.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, 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