Name Matching

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

2018-02 (month precision)Source: 02/2018

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

Name Matching - Identifies certain similarities in names across data sources. This allows staff to more easily compare information across data sources.

Expected benefits

Identifies certain similarities in names across data sources. This allows staff to more easily compare information across data sources.

System outputs

The system outputs a number which measures how closely names match.

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)

NEAT

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)

Aretec Inc

Vendors (standardized)

Aretec

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.sec.gov ↗

Authorization to Operate

Yes

Demographic features

k) None of the above

Training and evaluation data

Registrant 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