Agentic AI in Mortgage Servicing
AI agents that resolve borrower requests.
Resolve payoff requests, escrow questions, loss mitigation intake, and disputes — with a compliant audit trail at every step.









Deliver results for mortgage and loan servicers
Reduce inbound call volume, improve borrower satisfaction, and meet CFPB audit requirements without adding headcount.
Scale service without scaling headcount.
Automate the repetitive work – payoff statements, escrow breakdowns, and payment confirmations – so human agents focus on high-value interactions.
Reduce application drop-off
Assist potential borrowers through the application process, send proactive SMS to those that stall, personalized to where they need help.
Compliant by design
Every AI response is verified before delivery and logged to an immutable audit trail, so your compliance team has the record they need before anyone asks for it.
Built for every moment in the borrowers journey
From application through final pay-off, Quiq AI agents maintain full borrower context and complete compliance coverage at every stage of the loan.
Payoff processing
Authenticates, pulls a real-time calculation from your system, and delivers a certified payoff statement.
Escrow explanations
Walks line by line to explain the changes in escrow payments, accepts a catch-up payment over SMS.
Loss mitigation
Proactive outreach to explain options, collects hardship documentation, and routes an intake package to underwriting.
Application re-engagement
Assists with application process, sends SMS to reach borrowers that dropped off to help re-engage.
Payment status
Confirm payment posting, review history, and resolve late fee questions.
60%
requests resolved by agentic AI
The outcomes speak for themselves
Global brands trust Quiq to deliver faster resolution, with AI experiences that stay true to their brand.
Fast, accurate, compliant service at scale. See what it looks like.
Frequently Asked Questions (FAQs)
How does agentic AI improve mortgage servicing without adding compliance risk?
Agentic AI reduces risk when every response is checked against your actual servicing data before it reaches a borrower, not after. Quiq’s Verified Intelligence verifies each AI answer against your systems in real time, so payoff figures, escrow math, and policy statements are grounded in fact rather than generated from a language model’s best guess. Every decision is also logged to an audit trail your compliance team can pull on demand, which matters given how much scrutiny mortgage servicers face from the CFPB and GSEs on error resolution and loss mitigation. The result is automation that speeds up service without creating a new category of compliance exposure.
Can AI agents actually process a loan payoff, or do they just answer questions about it?
Quiq’s AI agents complete the payoff, not just explain it. The agent authenticates the borrower, pulls a live calculation from your servicing system, and delivers a certified payoff statement, the same task a servicing rep would otherwise handle by phone or email. This is the core distinction between agentic AI and a standard chatbot: a chatbot can tell a borrower how payoffs generally work, while an agentic system takes the actions needed to close the request out. Servicers using this approach have automated a majority of routine requests like this, freeing human teams for the exceptions that need judgment.
How does Quiq's AI handle sensitive borrower data securely during servicing conversations?
Borrower financial data, including loan balances, SSNs used for authentication, and payment history, stays protected through encryption in transit and at rest, plus a stateless AI architecture that doesn’t retain conversation data for model training. Quiq is SOC 2 Type II, GDPR, and CCPA compliant, and offers US and EU data hosting for servicers with data residency requirements. On top of that infrastructure, every AI response is verified against your grounded data before it’s sent, so borrowers never receive a fabricated balance or policy detail. Full details are in Quiq’s Security Overview
What's the difference between an AI chatbot and an agentic AI agent in mortgage servicing?
A chatbot answers questions. An agentic AI agent takes the next step: authenticating the borrower, checking a live system of record, and completing the transaction, whether that’s generating a payoff statement, processing an escrow catch-up payment over SMS, or routing a hardship package to underwriting. The difference shows up in outcomes. Quiq customers see a majority of borrower requests resolved by AI agents directly, not deflected back to a phone queue. For a deeper look at how agentic AI differs from deflection-style bots, see Quiq’s AI Agents overview
Can AI agents help with loss mitigation and hardship outreach, or is that too sensitive to automate?
Loss mitigation is one of the more sensitive parts of servicing, but that’s exactly where proactive AI outreach helps borrowers get options faster. Quiq’s AI agents can reach out to borrowers who may be at risk, explain the hardship programs available to them, collect the required documentation, and route a complete intake package to underwriting, all logged for compliance review. This isn’t a replacement for underwriting judgment; it’s faster intake so underwriters spend their time evaluating options instead of chasing paperwork. Given CFPB proposals aimed at streamlining payment-difficulty assistance, faster and better-documented intake is becoming a servicing expectation, not just a convenience.
How much of mortgage servicing volume can realistically be automated with AI?
Based on results from a leading mortgage servicer using Quiq, agentic AI resolved 60% of borrower requests without human involvement, covering payoff processing, escrow explanations, payment status checks, and application re-engagement. That figure reflects full resolution, not just initial contact deflection: the AI authenticates the borrower, completes the transaction, and closes the loop. The remaining volume, typically complex hardship cases or disputes, routes to human agents with full context intact, so nothing gets re-explained.

