Using Machine Learning/Artificial Intelligence Techniques to Predict Entities With Certain Risk Characteristics

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

2015-04 (month precision)Source: 04/2015

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

Analyze data to predict entities with certain risk characteristics. Staff may consider the results of these efforts in their examination efforts.

Expected benefits

Analyze data to predict entities with certain risk characteristics. Staff may consider the results of these efforts in their examination efforts.

System outputs

This system provides predictive information.

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)

EDP

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)

IBM

Vendors (standardized)

IBM

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

Filings and Examination 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.

Potential impacts and how they were identified

Not reported