Regulatory AI Agent
Complaint claims unauthorized fees, lack of transparency, and unclear communication of adverse decisions without proper explanation. This situation may necessitate a review based on disclosure, fairness, and adverse action criteria.
Analysts rely solely on their judgment to manually review complaints and transcripts in order to determine if an issue warrants legal or compliance consideration.
The agent detects potential signals related to laws, emphasizes the evidence, and directs relevant complaints to organized review processes.
Collect complaints, calls, emails, case notes, and supporting records from customer service and complaint-management systems.
Identify pertinent language, entities, fees, dates, adverse actions, unauthorized activity, or disclosure references within the complaint narrative.
Determine if the complaint involves UDAAP, TILA, FCRA, ECOA, or Regulation E by providing logical reasons and evidence.
Address appropriate cases, generate organized review findings, and assist investigators with synopses, evidence, and recommended actions.
Recognize grievances that could signal breaches or increased risk within financial services regulations and procedures for addressing complaints.
Associate evidence of complaints with applicable frameworks like UDAAP, TILA, FCRA, ECOA, and Regulation E, providing justification for the relevance of each law.
Identify the specific lines, statements, dates, or fee references that triggered the system to flag the complaint for potential review.
Rank complaints based on potential compliance importance to ensure teams address higher-risk cases and emerging patterns first.
Generate summaries, potential legal mappings, evidence trails, and proposed owners or workflows to support subsequent case systems.
Identify common complaints to uncover recurring issues that could point to broader policy, disclosure, servicing, or fairness concerns.
The agent is able to identify important patterns in regulated financial complaint processes, such as disclosure gaps, unauthorized transactions, adverse action language, billing disputes, servicing failures, and fairness concerns.
Compliance teams require judgment, but they shouldn't have to manually review every complaint to identify relevant ones. The agent filters the queue and records the reason for prioritizing a case.
We have the ability to conduct a trial using complaint data, emails, or call transcripts to demonstrate how the Regulatory AI Agent detects possible law-related signals, emphasizes the relevant evidence, and directs appropriate cases for compliance assessment.