Clearcover Insurance Company · AI Customer Servicing
AI servicing that cuts cost while raising satisfaction.
Clearcover Insurance Company now handles more than 17,000 customer contacts every month, and an AI servicing agent fronts every one of them — chat, mobile app, web, and phone, 24 hours a day. A significant share resolve fully before a person is ever involved. For the rest, the AI routes to a human advocate with full context. The AI does more than answer routine questions; it completes some policy administration transactions end to end, supports new customer inquiry, and takes action across channels. Human advocates handle the conversations that need judgment, licensing, and real expertise. After this implementation, servicing expense as a share of earned premium declined significantly, while customer satisfaction improved.
// Headline Numbers
Contact and CSAT figures sourced from Kimberly Barnes; servicing-expense ratio from Clearcover Finance.
Lower Servicing Expense
~45%
Servicing expense as a share of earned premium fell from 4.2% (Q1 2024) to 2.3% (Q1 2026) — nearly half. Source: Clearcover Finance.
Contacts Resolved by AI
~47%
Combined across chat, mobile, web, and voice. Unique contacts who resolved without reaching a human agent.
Hrs / Mo per Advocate
~17
Time previously spent on routine contacts, returned to each person on the servicing team. Nearly half a week, every month.
Monthly Conversations
17K+
Total AI-handled conversations monthly, across all channels and platforms.
CSAT Improvement
+24 pts
Improvement in predicted customer satisfaction versus the pre-deployment baseline, based on interaction analytics modeling.
Workflows in Production
8
The AI takes action, not just information retrieval. Cancellations, payments, vehicle adds, quotes, live policy status, and more. First workflow live within days of contracting.
Built With Clearcover Insurance Company
Carrier partners don't get Clearcover Insurance Company's servicing AI. They get their own agentic servicing layer, built on the same platform, the same approach, and nearly a decade of operating experience — tailored to their products, their systems, their compliance requirements, and their team. What Clearcover built, DL built with them. What you deploy, DL builds with you.
// The Challenge
Clearcover Insurance Company's servicing team handles more than 17,000 customer contacts each month across chat, mobile app, web, and phone. Contact types range from straightforward transactions — payment processing, policy lookups, billing inquiries — to situations requiring licensed advocate judgment, including cancellations, coverage questions, and billing disputes.
Prior to this deployment, the team's primary call-routing tool was an IVR that categorized contacts by menu selection. Routing was static: every inbound contact entered the same queue regardless of complexity or resolution path. There was no mechanism for separating high-judgment contacts from routine ones before a person picked up.
The consequence was a capacity problem. Advocates handled the full contact mix in the same queue. Contact volume was growing. Headcount was not scaling at the same rate. And servicing expense as a share of earned premium was climbing with the volume.
// The Approach
An AI servicing agent now fronts every customer contact across chat, mobile app, web, and voice. It was deployed channel by channel and built for speed to production. It resolves a wide range of complex issues end to end, from payments and policy lookups to full cancellation flows with built-in eligibility checks.
When a contact needs a person, it routes with context: the advocate sees what the customer needs, the relevant policy details, and the steps already completed, so they pick up mid-stream instead of starting from scratch. Customers no longer sit through a long, menu-driven phone tree — they simply tell the agent why they reached out. The legacy IVR is retired.
One design principle held throughout: compliance-aware routing is built into the workflow logic, not bolted on top. The moment a contact requires licensed judgment, coverage interpretation, or a regulated action, it routes to an advocate. The same deployment also instituted an AI Quality Assurance program: instead of a small human-scored sample, 100% of interactions are now scored by AI.
Kimberly Barnes · Gen AI Product Manager, Dearborn Labs
“Digitally native customers expect instant support, 24/7, but staffing to those expectations can be a challenge — and costly — for any insurer. That's why Clearcover turned to Dearborn Labs to build them an AI servicing experience. Dearborn Labs was able to meet customers where they're at, with higher satisfaction, higher quality outcomes, all for less cost.”
// By the Numbers — Deflection, Resolution & Satisfaction
Deflection, full resolution, and predicted satisfaction, by channel. Roughly 47% of all contacts — across chat, mobile, web, and voice — resolved without reaching a human agent, combined across 17,000+ monthly conversations.
Channel
Deflection
Full Resolution Rate
Predicted CSAT
Chat
74%
63%
74%
Voice
48%
33%
60%
The Signal
The Full Resolution Rate is the honest number. A 47% Full Resolution Rate means 47 out of 100 people who started a contact resolved it without ever needing to reach a human agent. That's 17 hours back to each advocate, every month. And the cost line moved with it: servicing expense as a share of earned premium fell from 4.2% to 2.3% over the deployment period — roughly 45%.
// What the Platform Does
Eight workflows in production. This is not a chatbot that surfaces FAQs. The AI takes action.
01
Payments & Billing
Generates a unique payment link on demand and answers account balance, payment history, and due-date questions. Routine payment and billing contacts close without an advocate.
02
Policy Status
Live policy details for authenticated users: coverage, effective dates, vehicle information, pulled in real time.
03
Add a Vehicle
Collects everything needed to add a vehicle, then routes to a licensed advocate. They pick up a complete package, not a blank intake.
04
Cancellations
Handles the full cancellation flow including eligibility checks. Compliance logic is built in, not bolted on.
05
Quote Assistance
Initiates new quote flows, then routes to licensed agents to bind. The AI starts. Licensed judgment closes.
06
Multilingual Chat
Chat support across languages. Contact volume doesn't segment by language; resolution capability now doesn't either.
07
Agent Portal Support
Producer-facing support on the internal agent portal. Administrative questions handled by AI. Licensed activities routed to licensed staff.
08
Outbound Engagement
Proactive outbound calling for prospects in the sales funnel. The AI initiates. Licensed agents close. 24/7, no staffing premium for off-hours.
// What Customers Ask
Sample customer requests handled by the platform.
>I need to make a payment
>What's my current coverage?
>I want to cancel my policy
>How much is my next bill?
>I need to add my son's car
>Can I get a quote for a new vehicle?
>Why was my payment returned?
>When does my policy expire?
>Has my claim been updated?
>I don't understand this charge
Aaron Wheaton · Chief Claims and Customer Service Officer, Clearcover Insurance Company
“We could not be happier with the team at Dearborn Labs. Their deep insurance expertise and operational skill made the implementation simple. It's not often you're able to reduce servicing expense while having happier customers, but that's exactly what Dearborn Labs delivered for us.”
// Methodology
Full Resolution Rate measures the percentage of unique contacts — callers or chatters — who resolved without contacting Clearcover Insurance Company again and reaching a human agent within 24 hours. It is more conservative than raw deflection rate, which counts all AI deflections including those where the customer later returned.
// The honest number. We report Full Resolution Rate, not raw deflection.
// Frequently Asked Questions
Common questions about AI customer servicing for insurance carriers.
What is Full Resolution Rate in insurance customer servicing?
Full Resolution Rate measures the percentage of unique contacts who did not contact the carrier again and reach a human agent within 24 hours of the original AI interaction. Unlike raw deflection rate — which counts all AI deflections including cases where the customer later returned — Full Resolution Rate excludes those callbacks. It is the more conservative and more accurate measure of genuine resolution. At Clearcover Insurance Company, the chat Full Resolution Rate was 63% and the voice Full Resolution Rate was 33%, for a 47% blended average.
What is the difference between deflection rate and full resolution rate in insurance servicing?
Deflection rate counts all contacts the AI handles before a human is reached, including contacts where the customer returned later. Full Resolution Rate counts only contacts where the customer did not return and reach a human within 24 hours. At Clearcover Insurance Company, the chat deflection rate was 74% but the Full Resolution Rate was 63% — 11 percentage points of “deflected” contacts ultimately came back. Full Resolution Rate is the number that holds up to scrutiny. It is Clearcover Insurance Company's primary internal metric and the one used throughout this case study.
Does AI customer servicing hurt customer satisfaction scores at insurance carriers?
No. At Clearcover Insurance Company, predicted CSAT improved by 24 points following deployment. Chat CSAT reached 74% and voice CSAT reached 60% based on April 2026 interaction analytics. The assumption that AI servicing and high customer satisfaction are in tension did not hold in production. When AI resolves routine contacts correctly and routes complex contacts with context, customers reach the right resource faster — and advocates spend more time on the conversations that require their expertise.
Does AI customer servicing reduce cost for insurance carriers?
At Clearcover Insurance Company, servicing expense as a share of earned premium fell from 4.2% (Q1 2024) to 2.3% (Q1 2026) — roughly a 45% reduction — over the AI servicing deployment period, while customer satisfaction improved. Servicing expense as a share of earned premium measures what it costs to service policies relative to premium earned; it is distinct from claims or loss costs.
What insurance servicing workflows can AI handle without a human agent?
An AI servicing agent can handle payment processing, policy status lookups, billing inquiries, cancellation flows with eligibility checks, vehicle additions, quote initiation, multilingual chat support, and producer portal support without human intervention. At Clearcover Insurance Company, eight action-oriented workflows are in production — the AI takes action, not just information retrieval. Contacts requiring licensed judgment route to licensed advocates with full context on the contact.
How much time does AI customer servicing return to insurance advocates per month?
At Clearcover Insurance Company, the AI servicing deployment returned approximately 17 hours to each advocate every month — nearly half a workday per week. Across the servicing team handling more than 17,000 monthly contacts, that totals 483 advocate hours per month freed from routine contacts. That time is available for contacts requiring licensed judgment: coverage questions, billing disputes, and situations that require a person.
How quickly can an AI servicing agent go live at an insurance carrier?
At Clearcover Insurance Company, the first AI servicing use case went live within days of contracting. Seven workflows were in production within 90 days. Eight are running today. Speed depends on how well-defined the initial use case is and how accessible the carrier's contact and policy data are. The deployment model is designed for rapid iteration: a payment-by-link or policy status workflow can go live quickly and immediately reduces inbound contact volume on the advocate team.
// Interested in deploying this?
Clearcover Insurance Company is the insurance carrier referenced in this material. Dearborn Labs is an affiliate within the Clearcover Insurance Holdings family. Dearborn Labs is not an insurance company and is not licensed to adjust insurance claims. All coverage, liability, and settlement determinations referenced in this material were made by Clearcover Insurance Company's licensed adjusters. Results reflect Clearcover Insurance Company's deployment. Outcomes for other carriers will vary based on contact volume, channel mix, system integrations, and deployment scope. Prospective customers should evaluate results in light of their own operations, jurisdictional requirements, and applicable regulatory environment. Dearborn Labs does not issue, underwrite, or sell insurance, and nothing in this material is an offer of insurance or a representation of coverage. Copyright 2026 Clearcover, Inc. All Rights Reserved.