New Data Package: License PolicyMap’s Housing and Community Development Finance Data

A new curated data package focused on Housing and Community Development Finance is now available for license from PolicyMap. Drawing on more than 80 U.S.-based data sources, the collection covers federal housing and community development programs — including New Markets Tax Credits (NMTC) and the Community Reinvestment Act (CRA) — as well as housing market conditions and affordability, mortgage activity, housing stock characteristics, and community risks and assets. Data is harmonized across a wide range of geographies, from Census tracts and ZIP codes up to states and metro areas.

Included Sources

The package draws on authoritative sources, including:

• U.S. Census Bureau
• U.S. Department of Housing and Urban Development (HUD)
• Moody’s Analytics
• CDFI Fund
• Environmental Protection Agency (EPA)
• FEMA
• Many unique indicators created by PolicyMap

Use Cases

Our analytics-ready data helps community development organizations, financial institutions (including CDFIs and credit unions), and state and local government agencies examine the market and demographic trends shaping housing supply and housing needs across the U.S. Common use cases include market studies, housing and community needs assessments, strategic planning, and impact reporting. All of our data can also be integrated with internal lending or project information to verify federal program eligibility, align investment resources with areas of need, and quantify impact.

Business Needs

Investment Analysis

• Use cleaned, analytics-ready datasets to track investments in federally designated underserved communities, covering programs such as Opportunity Zones, New Markets Tax Credits (NMTC), and the Community Reinvestment Act (CRA).

• Measure lending equity across demographic and socioeconomic groups, and produce defensible impact metrics for stakeholders and regulators.
• Identify tracts where new housing is most severely needed in the U.S.

Location Planning

• Enhance market coverage by identifying and targeting underserved regions.
• Strategically plan lending and development opportunities by identifying areas with the greatest market needs.

Market Analysis

• Understand housing market conditions at a granular level with indicators ranging from housing gap estimates to affordability, cost burdens, mortgage activity, and community demographic context.

• Quickly access the core quantitative data needed for housing needs assessments and community plans.

Machine Learning

• Improve machine learning models by enriching them with contextual information about housing market conditions, housing stock, community risks, community assets, lending activity, and demographic and socioeconomic context — leading to more accurate predictions, better risk stratification, and enhanced decision-making.