# Every call scored against your SOPs and the regs. Nothing sampled. *Call Monitoring* > Sei encodes your rulebook — including the edge cases that live in your reviewers’ heads — and scores every interaction against it, with the violating moment cited to its timestamp. ## The desks Call Monitoring powers - **[Compliance Agent](/for-lenders/compliance-agent)** — Every loan-officer call scored, none sampled - **[Compliance Manager](/for-servicers/compliance-manager)** — Every servicing call and letter scored ## Every interaction, end to end 1. **Ingest** — Calls, emails, chats and external review channels land in one record per interaction, transcribed and attributed turn by turn. 2. **Score** — Each interaction is scored against your SOPs, your QA rubric and the regulations that apply to it — across more than thirty dimensions 3. **Surface** — Violations, coaching opportunities and complaint trends reach your team with a severity score and the moment in the conversation that produced them. ## Proof Better Mortgage audits LO calls with a compliance agent built with mortgage regulations. - **1,000+** — calls audited per month - **4×** — analyst productivity - **0%** — Sampling & Manual review rate Call auditing went from 4 a day, against a backlog of more than 1,000, to a full month of calls scored in under an hour — with **no sampling**. [Read the case study](/case-study/sei-x-ny-mortgage-lender) ## Demo [Call Monitoring on a scored interaction](https://www.youtube.com/watch?v=hHmJjpoqRPY) — A scored conversation with the findings beside it — what was flagged, under which rule, and where. ## The channels it scores, and what it scores them on ### Channels it scores - Inbound and outbound calls - Email - Chat - CFPB Consumer Response complaints - Trustpilot and the BBB - App Store and Play Store reviews ### What each interaction is scored on - Regulatory exposure — TILA, RESPA, TRID, UDAAP, FDCPA, TCPA, ECOA and Fair Housing - Process adherence to your SOPs - Disclosure and script compliance - Customer experience and sentiment across the call - Complaint identification, disposition and resolution ### What comes out - A scorecard per agent, with coaching recommendations - The violating moment cited to its timestamp in the transcript - Complaint categories and trends across channels - Severity-scored findings pushed to your team ## What sets it apart - Every interaction scored, not a 3% spot-check - Your QA rubric encoded, including the edge cases that only live in reviewers’ heads - The violating moment cited to its timestamp, so a reviewer goes straight to it - Complaints tracked across the CFPB portal, Trustpilot, the BBB and the app stores **1,000+** — calls audited a month, none sampled ## When it is unsure A scored interaction that sits near a rubric boundary is flagged for a human reviewer rather than silently passed or failed. ## FAQ **What does 100% coverage actually mean here?** Every call, email and chat, not a sample of them. Our customers have gone from auditing a few loan-officer calls a day to running every call through Sei — with no sampling and no manual review queue. **How is this different from the QA scoring in our contact-center platform?** The rubric is a mortgage rulebook — TILA, RESPA, TRID, UDAAP, FDCPA and your own SOPs, including the edge cases your reviewers carry in their heads — rather than a generic quality score. And every finding cites the moment in the conversation that produced it, so a reviewer verifies it real-time instead of relistening to the call. **What happens to a score that sits near a boundary?** It is flagged for a human reviewer rather than quietly passed or failed, with the moment cited so the reviewer can go straight to it. **Where do the complaints come from?** The CFPB Consumer Response portal, Trustpilot, the BBB and the app stores, alongside the complaints raised in your own calls, emails and chats. They are categorised and trended together, so a trending issue surfaces as a pattern. ## The rules a conversation is scored against - [UDAAP for AI Agents in Consumer Finance: What "Materially Interferes" Actually Looks Like in a Chat Transcript, and the Consumer-Experience Test the CFPB Applies](/blog/udaap-ai-agents-consumer-finance-cfpb-1031-1036) — UDAAP is the rule every consumer-facing AI system in banking is ultimately measured against, and it is also the rule with the least specific text. The CFPB's Circular 2023-03 on chatbots, the 2022 exam manual update that was later rescinded, and the enforcement pattern under 12 USC 5531 and 5536 set the practical standard the agent has to clear. What we score against on every conversation, and why the consumer-experience test is the one that matters more than the internal QA test. - [The CFPB Consumer Response Portal With AI Complaint Handling: The 15-Day and 60-Day Response Windows, the Portal Tag Discipline, and the Public-Database Read the Bank Cannot Ignore](/blog/cfpb-consumer-response-portal-ai-complaint-handling-15-60-day) — Every complaint routed through the CFPB Consumer Response portal is a supervised, time-boxed compliance event with a 15-day acknowledgment, a 60-day substantive response, a specific issue-and-sub-issue taxonomy that becomes the public database, and a consumer-dispute flag the Bureau tracks. The rule reads simple and the operations misfire often. Where the AI agent tightens the intake, the response drafting, and the root-cause loop, and the audit file the Bureau tests against in an examination. - [AI Call Monitoring for Regulated Finance: A Practical Guide](/blog/ai-call-monitoring-regulated-finance) — How AI call monitoring moves beyond speech analytics to policy-aware, end-to-end monitoring with real-time nudges, complaint detection, and audit-ready evidence. --- _Source: [https://www.seiright.com/platform/call-monitoring](https://www.seiright.com/platform/call-monitoring) · Sei AI_