Topic archive
Research and practical notes filed under this topic.
December 15, 2025
AI tools used in collections remain subject to existing consumer-protection requirements, while new state AI rules vary sharply by jurisdiction, timing, and the type of organization involved. This guide separates current requirements from forthcoming Colorado and California obligations and outlines practical controls for AI-assisted collection workflows.
Read the analysisDecember 12, 2025
AI vendors can support collection operations, but a product demonstration is not evidence that a tool can be used safely in a regulated workflow. This guide explains how to assess AI systems for consumer-facing collections by mapping their functions to applicable controls, testing their outputs, and documenting human oversight.
Read the analysisDecember 9, 2025
AI can help collection and accounts-receivable teams sort work, draft supervised communications, and detect process exceptions, but it should not be treated as the final compliance decision-maker. This guide outlines a controlled deployment process, practical metrics, and U.S. consumer-debt and data-security considerations.
Read the analysisNovember 20, 2025
Generative AI can support narrow debt-collection tasks, but it should not be permitted to invent account facts, make unapproved commitments, or communicate outside established controls. For organizations covered by federal debt-collection rules, a sound program pairs approved data and rules with human escalation, testing, monitoring, and records; state law and the facts of each workflow still matter.
Read the analysisNovember 13, 2025
AI can help collections teams prioritize work, standardize approved workflows, and surface items for review, but it does not remove the need for accountable human oversight. This guide explains practical controls for scoring, communication workflows, validation and dispute routing, and AI governance in U.S. consumer debt collection.
Read the analysisFebruary 10, 2023
Collection automation can reduce repetitive administrative work, improve task handoffs, and give staff better account context. The strongest designs treat communication limits, consumer preferences, data quality, exception routing, and audit records as workflow requirements rather than after-the-fact checks. This guide outlines a practical approach for receivables operations, with added care for consumer-debt workflows.
Read the analysisApril 25, 2018
Artificial intelligence can help banks organize collection workflows, but it does not remove the need for accountable judgment, tested controls, or consumer protections. For APAC operations, the practical starting point is a governed use case that is reviewed against the rules of each jurisdiction where the bank, customer, data, and communication channel are located.
Read the analysis