Smarter, faster loan reviews
KPMG helped the U.S. Federal Housing Administration protect against losses with user-friendly technology and streamlined processes.
Client
U.S. Department of Housing and Urban Development – Federal Housing Administration
Sector
Federal government
Project
Mortgage loan risk and fraud loan review system
Client challenge
The largest insurer of mortgages in the world, the U.S. Department of Housing and Urban Development Federal Housing Administration (FHA), has served the country’s lending needs since 1934. For the FHA to easily engage with the lender community and adapt to changing policies and regulations within the mortgage market, they needed a modernized Loan Review System (LRS).
The FHA’s postendorsement loan review process was manual, paper-based, and supported by a legacy mainframe-based application. This approach made conducting business difficult. Reviews and staff workload management were inconsistent across the country, limiting the number of loans the FHA could review each month. Furthermore, changes to the legacy application to meet evolving policies and requirements were costly and time consuming.
The loan review process needed an overhaul to increase the FHA’s capabilities, proactively respond to changes, and empower the organization. We collaborated with alliance partner, Microsoft, to collaborate and help assess the FHA’s business needs.
Using our proprietary CYCLE tool, client stakeholders were able to engage in the design process from anywhere and understand early how the system would look and work.
Approach
The FHA needed to protect against losses from mortgage loan default by creating an updated, well-organized loan review process focused on review efficiency through workflow automation and business rules. Drawing upon KPMG’s strong insights and knowledge combined with Microsoft’s innovative technologies, we worked in tandem with the client to bring the LRS to life with a user-centric design approach and an agile development methodology.
We designed all LRS screens in the first six weeks of the project using our proprietary Cycle tool that allowed stakeholders to engage in the design process from anywhere, and understand how the system would look and work before writing a line of code. Training for the FHA and the lender community was completed early on to help ensure a smooth launch.
With this system in place:
1
The FHA now has the capabilities to pull from a new Enterprise Data Management (EDM) Solution, built by KPMG in parallel to LRS, which consolidates data from numerous source systems.
2
The EDM solution is built using Big Data Architecture in HUD’s Microsoft Azure cloud and enables systems to use services to pull data from a centralized location rather than perpetuating point-to-point interfaces.
3
LRS is the first system developed using the EDM solution and allows FHA to continue to review loans for risk, but with consistency and a greater focus on standardization, transparency, and regulatory requirements. LRS enables the FHA to adapt to frequently changing policies and regulations within the mortgage market, helping to ensure the lender community is complying with the organization’s underwriting standards. Empowered and adaptive, the FHA can now better serve the lending needs of the country.
Benefits to client
By building a streamlined, modern LRS using open source technologies and hosted on a Microsoft Azure Private Cloud, the FHA has dramatically improved the way they review loans for risk and fraud. They can now engage with the lender community through a well-designed user interface and a set of business rules maintainable by the FHA. The system’s benefits include:
1
Standardized user interface for an enhanced and consistent user experience.
2
Automated workflow, determining next steps in the loan review process based on a reviewer’s decision making.
3
Reduced paper, allowing lenders to upload supporting documentation directly to the system as HUD moves to a paperless LRS.
4
Automated assignment, matching review location and reviewer skills/availability with loans based on loan data.
5
Selection algorithm, selecting loans for review based on defined risk factors using loan data.
6
Adaptable and scalable design, allowing business administrators to change attributes within the system without needing to write a single line of code.
7
Robust reporting solution, allowing internal and external transparency.
Meet our team
Ty Enmark
Principal, Federal Advisory, KPMG US
Ty Enmark
Principal, Federal Advisory, KPMG US