FDIC · FDIC – 21 · record R1054
HMDA (Home Mortgage Disclosure Act) Outlier Screen
Federal Deposit Insurance Corporation · Division of Depositor and Consumer Protection
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
- 2019-01 (month precision)Source: 01/2019
- Withheld from public reporting
- NoSource: a) No
Mission
- Topic area
- Other
- Operational functions
- No function tag matched Derived by keyword rules; see methodology
Problem the AI is intended to solve
Scoping fair lending examinations can be time intensive.
Expected benefits
The HMDA (Home Mortgage Disclosure Act) program pre-screens off-site mortgage data to allow better utilization of examiner time on the highest risk areas and provides a data driven, objective basis to determining risk identification.
System outputs
DCP Exams receives a report identifying areas of heightened risk of consumer harm.
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)
- PERSYS
- 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
- Yes
- Privacy Impact Assessment
- www.fdic.gov ↗
- Authorization to Operate
- Yes
- Demographic features
- a) Race/Ethnicity; b) Sex; c) Age
- Training and evaluation data
- Regulatory Home Mortgage Disclosure Act (non-public) data is analyzed with supervised learning using SAS 9.4.
- 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