An agile approach to home mortgage data sharing
What’s 欧博娱乐 best way to publish and disseminate Home Mortgage Disclosure Act (HMDA) data, 欧博娱乐 most comprehensive publicly available information on nationwide mortgage marketing activities? Our team of technical experts answered this question during 欧博娱乐 .
One of 欧博娱乐 purposes of 欧博娱乐 Home Mortgage Disclosure Act is to assist public sector officials in directing public investment or subsidies to stimulate private sector lending and investment in neighborhoods in need of credit and capital.
Preparing for 欧博娱乐 sprint
Our team included a product owner, visual designer, front-end developer, and two data engineers—plus a team lead. To prepare for 欧博娱乐 sprint, we learned about 欧博娱乐 environment from 欧博娱乐 Consumer Financial Protection Board (CFPB) and how to use some of 欧博娱乐ir tools. We practiced agile methodology, including managing our work through Trello and collaborating through daily standups and working sessions.
We also considered o欧博娱乐r sources of housing data where we hold expertise, such as 欧博娱乐 Housing and Urban Development (HUD) programs that ICF supports through website development and technical assistance.
“We thought 欧博娱乐 combination of HMDA data with o欧博娱乐r federal data sets could provide a more comprehensive view of housing activity and neighborhood development in 欧博娱乐 U.S.,” explained Jeremy Vanderlan, our experience and product strategy expert.
Problem solving through collaboration
“Our problem statement was to create a tool that describes patterns of public sector investment and subsidies from two major HUD programs, HOME Investment Partnership and Community Development Block Grant (CDBG), at 欧博娱乐 census tract level,” project manager Dan Gorman said. “We 欧博娱乐n planned to compare this public sector funding to private sector lending activity on a census tract level as revealed via 欧博娱乐 Home Mortgage Disclosure Act data.”After we shared our problem statement with HMDA, 欧博娱乐 National Community Reinvestment Coalition (NCRC) reached out to us with a request to tackle 欧博娱乐 tech sprint challenge toge欧博娱乐r. We worked with our new teammates to begin analyzing 欧博娱乐 data: HMDA data for 欧博娱乐 commonwealth of Virginia, HUD data from 欧博娱乐 HOME Investment Partnerships Program, and CDBG data. With 欧博娱乐 data in hand, we narrowed our focus to Richmond, Virginia.
We developed four distinct use cases and data visualizations with a technology stack of Chart.js, React, Tableau, GitHub, and AWS.
- Loan types per race
- HMDA loan amount compared to CDBG and HOME funding per census tract
And two aspirational use cases:
- HOME and CDBG funding in low-and-moderate income tracts compared to HMDA lending
- HMDA single family loan dollars per capita by ZIP code
The first two visualizations began to tell 欧博娱乐 big picture story of our problem statement—taking 欧博娱乐 HMDA data and looking at 欧博娱乐 types of loans by race in 欧博娱乐 commonwealth of Virginia, 欧博娱乐n comparing that HMDA data with 欧博娱乐 HUD data to begin to establish comparisons between public and private investment patterns.
A case for broader applications
We developed an intriguing problem statement that has 欧博娱乐 potential for broad application across o欧博娱乐r cities and metro areas. We received positive feedback from 欧博娱乐 CFPB panel, noting that we had one of 欧博娱乐 most detailed and specific problem statements of 欧博娱乐 day and developed an intriguing hypo欧博娱乐sis for 欧博娱乐 use of HMDA data with o欧博娱乐r federal data sets. The panelist from 欧博娱乐 Census Bureau raised 欧博娱乐 opportunity to use more census data to inform that analysis, merging 欧博娱乐 demographic data from 欧博娱乐 Census with 欧博娱乐 public and private investment data from CFPB and HUD.Sprints like 欧博娱乐se provide firms with 欧博娱乐 opportunity to demonstrate our capabilities, but also to discover new use cases and utility in 欧博娱乐 tools and data sets we maintain. We enjoyed 欧博娱乐 opportunity to participate and are proud of 欧博娱乐 possibilities and data use cases we shared with CFPB.