Auditing Diversion Registrant Inventories of Controlled Substances

Overview

Development stage

In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.

High-impact designation

Not high-impactSource: c) Not high-impact

Impact justification

Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.

Start date

Not reported

Withheld from public reporting

NoSource: a) No

Mission

Topic area

Law Enforcement

Operational functions

No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Diversion Investigators regularly conduct accountability audits of Registrants' management of controlled substances in order to detect diversion. Registrants sometimes submit hundreds of pages of invoices, receipts, and logs, which must be reconciled against inventory and movement records to ensure that the audits balance. Diversion Investigators review these and mark them for review if there is non-compliance with regulations, such as missing information or missed signatures. This current workflow relies on manual data entry into spreadsheets, leading to errors, inconsistencies, and excessive investigative time.

Expected benefits

Reduces the amount of investigator time per audit by automating the extraction of key fields (e.g., item, quantity, cost, dates) from invoices and auto-populating computation charts. Standardized extraction and reconciliation eliminates human entry errors and decreases audit reconciliation error rates. Real-time flagging of discrepancies (e.g., inventory errors, excess sales, mismatched destruction records, possible fraudulent records) hastens the detection of potential diversion. Frees investigators to focus on high-value investigative activities and field operations, saving thousands in costs. Provides an auditable trail of extraction and reconciliation for internal and external audits. Maintains full audit-ready compliance for all registrants and a tangible audit trail for legal proceedings.

System outputs

Outputs may be data reports to support Diversion Control Division's mission and better serve the registrant community.

Technology

AI classification

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

System name(s)

Not reported

Custom-developed code

Not reported

Public source code

Not reported

Sourcing

How it was built

Not reported

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

Not reported

Privacy Impact Assessment

Not reported

Authorization to Operate

Not reported

Demographic features

Not reported

Training and evaluation data

Not reported

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