FHFA · FHFA-2 · record R0068
Neural Networks for FHFA Modeling Analytics Platform (FMAP)
Federal Housing Finance Agency · DHMG
Overview
- Development stage
- DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
- High-impact designation
- Not high-impactSource: c) Not high-impact
- Impact justification
- Not reported
- Start date
- 2024-01-05 (day precision)Source: 01/05/2024 00:00:00
- Withheld from public reporting
- NoSource: a) No
Mission
- Topic area
- Information Technology
- Operational functions
- Forecasting and prediction Derived by keyword rules; see methodology
Problem the AI is intended to solve
Help researchers optimize the framework and specifications of the production of the Single-Family FHFA Modeling Analytics Platform (FMAP).
Expected benefits
Efficiency
System outputs
This tool uses neural networks to identify nonlinearities, anomalies, and important variables in loan-level mortgage data, which helps FHFA staff improve forecasts from the Single-Family Modeling Analytics Platform.
Technology
- AI classification
- Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
- System name(s)
- Not reported
- Custom-developed code
- Yes
- Public source code
- Not reported
Sourcing
- How it was built
- Developed in-houseSource: b) Developed in-house
- Vendor (as reported)
- Not reported
- Vendors (standardized)
- None on the standard list
A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.
Data and privacy
- Involves PII
- No
- Privacy Impact Assessment
- Not reported
- Authorization to Operate
- No
- Demographic features
- i) Income
- Training and evaluation data
- MLIS - Borrower level monthly mortgage data
- Federal Data Catalog
- Not reported
Governance
0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.
Pre-deployment testingNo answer reported
AI impact assessmentNo answer reported
Independent reviewNo answer reported
Ongoing monitoringNo answer reported
Operator trainingNo answer reported
Fail-safeNo answer reported
Appeal processNo answer reported
User and public consultationNo answer reported
Potential impacts and how they were identified
Not reported