Risk Rating Model

Overview

Development stage

PilotSource: b) Pilot – The use case has been deployed in a limited test or pilot capacity.

High-impact designation

Not high-impactSource: c) Not high-impact

Impact justification

Not reported

Start date

2019-10-02 (day precision)Source: 2019-10-02T00:00:00

Withheld from public reporting

NoSource: a) No

Mission

Topic area

Other: Economic & FinancialSource: Other – Economic & Financial

Operational functions

Risk scoring and triage Derived by keyword rules; see methodology

Problem the AI is intended to solve

Improve risk models optimize resource allocation

Expected benefits

Identify a set of factors that may be helpful in predicting the likelihood that a bank will experience an adverse outcome in the future, and to tier banks into High-, Moderate- and Low-risk tiers for review

System outputs

Statistical methods are used in the variable selection process for a risk model

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)

General Support System

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

Yes

Demographic features

k) None of the above

Training and evaluation data

Internal – FFIEC Call Report, Uniform Bank Performance Report

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