Normalization Services
Description
This use case intends to solve the problem of data redundancies, inconsistencies difficult to integrate data that hinders the efficiency and accuracy of investigations.
Detailed example
The output includes normalized data that improves search capability during investigations. This includes normalizing data to update less well-defined addresses into usable addresses for analysis- (such as those using mile markers instead of a street number); inferring ID type based on user-provided ID value (such as distinguishing a SSN from a DL number without additional context); categorizing name parts while taking into account additional factors (including generational suffixes and multi-part family names); and validating and normalizing phone numbers to the E164 standard, including their identified county of origin.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
HSI utilizes artificial intelligence to enhance data accuracy and efficiency by verifying, validating, correcting, and normalizing various types of information, including addresses, phone numbers, names, and ID numbers. This process helps to eliminate data entry errors, detect intentional misidentification, and connect related information across multiple datasets, ultimately reducing the time and resources required for investigations. The machine learning-powered normalization services offered by HSI include converting ambiguous addresses into usable formats, identifying ID types from partial information, categorizing names with complex suffixes and family names, and standardizing phone numbers to the E164 format, including determining their originating county. By normalizing and improving the quality of investigative datasets, HSI is able to use more advanced tools to find correlations and leads that would have otherwise gone undetected without extensive manual effort.
Controls / human review
ATO: Yes; PIA: https://www.dhs.gov/sites/default/files/2025-06/25_0618_priv_pia-ice-055-raven-appendix-update.pdf
Data needed
Data holdings within HSI case files that require normalization (e.g. subpoenaed phone record). This includes, but is not limited to, evidentiary records containing phone numbers, names, addresses, and ID numbers.