Counterparty Risk Anomaly Detection

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

2022-05-01 (day precision)Source: 2022-05-01T00:00:00

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

Ginnie Mae is responsible for analyzing counterparty risk profiles of mortgage issuers who participate in Ginnie Mae’s program. Ginnie Mae analyzes data from multiple sources to identify potential risks and areas of focus.

Expected benefits

To enhance the identification of data patterns, Ginnie Mae uses machine learning algorithms, specifically clustering and genetic techniques. These algorithms detect potential risk areas, enabling a focused approach to subsequent analysis by Ginnie Mae staff.

System outputs

Data patterns

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)

Ginnie Mae Reporting and Feedback System (RFS)

Custom-developed code

Yes

Public source code

Not reported

Sourcing

How it was built

Contract and in-houseSource: c) Developed with both contracting and in-house resources

Vendor (as reported)

Deloitte Consulting, LLC

Vendors (standardized)

DDeloitte

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

Yes

Demographic features

k) None of the above

Training and evaluation data

This is not a self-learning system. Although the data is not used to train, fine-tune, and/or evaluate performance, the following sources are used by the ML model to perform analysis: - Ginnie Mae (GNMA) Investor Reported Mortgage-Backed Securities (MBS) portfolio data aggregated on an issuer level - MBFRF (Mortgage Banking Financial Reporting Form) Data for counterparty financial information

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.

Potential impacts and how they were identified

Not reported