How AI can support recovery
Models may analyze account history, classify incoming messages, summarize conversations, or recommend a next step. Generative AI may draft a response using approved account facts and guidance.
Rule-based automation follows predefined conditions. AI uses learned patterns or generated outputs, so its recommendations can be uncertain or incorrect. Many collection workflows combine both.
A practical workflow
A system might flag an account for review after a broken payment promise. A collector checks the balance, recent receipts, any dispute, and permitted options before approving the next step. A prediction alone does not establish ability to pay or authorize a legal action.
Controls and measurement
Use verified data, access restrictions, approved messaging, escalation paths, and records of consequential decisions. Test outputs for factual errors and inappropriate treatment, and monitor performance after deployment.
Evaluate recovery outcomes alongside complaints, disputes, cost, and model errors. AI does not guarantee higher recovery, accurate balances, or legal compliance.
The NIST AI Risk Management Framework provides a voluntary approach to assessing and managing AI risks; it is not a certification of a collection workflow.