Extracting IT Information

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

2018-01 (month precision)Source: 01/2018

Withheld from public reporting

NoSource: a) No

Mission

Topic area

Information Technology

Operational functions

Search and knowledge retrieval Derived by keyword rules; see methodology

Problem the AI is intended to solve

Searching for information using AI rather than manual reviews of pdf documents or using the RADD search function. AI simplifies the search efforts with a more robust search engine and provide better potential hits of desired information much faster than the current methods.

Expected benefits

Algorithm, Language Processing Horizontal Analysis - Risk Examination (AlphaREx) analyzes unstructured narrative content in Information Technology (IT) examination workpapers and Reports of Examination (ROE) to provide meaningful, actionable insights into information. AlphaREx capabilities contribute to the FDIC’s Modernization initiative for the Supervision Modernization Business Drivers and supports the mission of the RMS Information Technology Section.  Additionally, AlphaREx was developed to enable the automation, ingestion, analysis, and visualization of the information technology and operational unstructured and structured data gathered per the supervised financial institution.

System outputs

Information collected across the IT Profile, FDIC Review of Examinations (ROEs), and multiple other sources (both unstructured/structured data) is a critical business need and is used by FDIC to promptly identify and address IT risks and Cyber risks for the FDIC Insured Deposit Institutions (IDIs).  In addition, this information is used to effectively identify trends, patterns and areas of improvement for the InTREx program; including training and changes to the FDIC IT Examination processes.

Technology

AI classification

Natural language processingSource: Natural Language Processing: AI that processes, interprets, and shares information in human language.

System name(s)

AlphaREx

Custom-developed code

Yes

Public source code

various code libraries to include the following: beautifulsoup4 chardet cx_Oracle dask datefinder==0.7.1 docx2txt flask gensim==4.0.0 GitPython lxml matplotlib >= 3.7 nltk==3.6.7 numpy >= 1.24 pandas<2.0 pyarrow >= 11.0 pyodbc python-dateutil python3-saml rapidfuzz scikit-learn<1.2 scipy >= 1.10 sentence-transformers >= 2.2 # snappy==1.1.10 # Spacy 3.0 is incompatible with AlphaREx spacy_setup.py. nlp.add_pipe now takes the string name of the registered component factory, not a callable component. # Spacy 2.3.7 runs with python 3.9 without crashing, but yields different pipeline results. spacy==2.2.4 statsmodels tabulate torch # Additional Packages used during software development autoflake black==22.3.0 build bump2version coverage flake8 isort==5.11.5 jupyter locust >= 2.19 mypy pip pre-commit pylint pytest pytest-cov pyupgrade ruff # Packages installed with pip when using conda detect-secrets docx2python flask-paginate gunicorn line_profiler qdrant-client sphinx sphinx-rtd-theme transformers>=4.3

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

k) None of the above

Training and evaluation data

Examination documents

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