A minor collision during rush hour.
A tree crashing through a roof in a storm.
A kitchen fire that escalates in minutes.
For insurance policyholders, these events trigger immediate uncertainty and stress: What should I do next? Who can help me? How long will this take?
The first interaction following an incident—the First Notice of Loss (FNOL)—is one of the most consequential moments in the insurance experience. According to J.D. Power, FNOL accounts for 26% of the overall customer satisfaction index. This single interaction sets expectations for the entire claims journey. When handled well, it builds confidence and trust. When handled poorly, it can permanently damage the relationship.
The stakes are high. Research from Accenture shows that 83% of customers switch providers after a negative claims experience. For insurers, this makes the contact center not just a service function, but a critical driver of retention and brand perception.
The operational pressure facing insurance contact centers
Insurance contact centers operate under uniquely difficult conditions. Agents must support distressed policyholders, collect accurate information quickly, navigate multiple systems, and ensure regulatory compliance, all while delivering empathy, speed, and precision.
Three operational challenges intensify this pressure:
1. High-emotion interactions at critical moments
FNOL calls are fundamentally different from routine service inquiries. Policyholders may be calling from the roadside after an accident or from their home during an active emergency. These are crisis interactions, not transactional conversations. Customers expect immediate assistance, clear guidance, and minimal friction, without transfers or long hold times.
2. Complex documentation across disconnected systems
Claims intake requires detailed information that must be recorded across policy administration systems, claims management platforms, fraud detection tools, and payment systems. Agents often toggle between multiple applications, each with its own interface and login, while manually re-entering data as policyholders wait. This complexity increases handling time and introduces errors.
3. Extreme volatility in claim volume
Weather events and natural disasters can multiply claims volume overnight. Hurricane season, winter storms, and wildfires create sudden, sustained demand spikes that are difficult to staff for efficiently. Insurers are left to choose between maintaining costly excess capacity or risking service breakdowns during moments when policyholders are most vulnerable.
AI agents are well suited to address these challenges, particularly in high-volume, time-sensitive interactions where speed and accuracy directly influence customer trust.
Use Case 1: First Notice of Loss (FNOL) intake
Consider a policyholder involved in a rear-end collision. They are shaken but uninjured and call their insurer seeking immediate guidance. They want reassurance, clarity on coverage, and a clear understanding of next steps.
This initial FNOL interaction is the foundation of the entire claims experience. Beyond its contribution to overall satisfaction, 87% of policyholders report that the claims experience influences their decision to remain with their insurer.
Limitations of a human-only approach
During peak periods, policyholders often wait on hold before reaching an agent. Once connected, the agent must gather extensive information: policy and identity details, incident specifics, third-party information, damage assessments, and supporting documentation such as photos.
This information is manually entered across multiple systems while the policyholder repeats details and answers follow-up questions. Agents switch between policy verification tools, claims platforms, and fraud systems, slowing resolution and increasing friction.
The impact is measurable:
- Elevated stress: Long wait times and repeated questioning intensify anxiety during already distressing situations
- Data quality issues: Stress impairs recall, and manual entry increases the risk of missing or incorrect information. A Pollfish survey found satisfaction drops from 86% when details are shared once to just 7% when repeated six or more times
- Operational inefficiency: Agents must navigate numerous systems with inconsistent workflows and credentials, extending handle times and reducing capacity
How AI agents improve FNOL intake
With an AI agent, the policyholder is immediately connected, without any wait time. The AI verifies identity, collects incident details conversationally, confirms coverage, creates the claim, uploads supporting documentation, and assigns an adjuster in real time.
The policyholder receives a claim number, clear next steps, and an expected timeline. Adjusters receive complete, structured, and accurate data with no follow-up required.
Business impact:
- Immediate response during crisis moments
- Accurate, structured data captured across systems simultaneously
- 24/7 FNOL coverage without staffing surges during catastrophic events
FNOL addresses the initial crisis. The next challenge emerges in the days and weeks that follow.
Use Case 2: Claims status inquiries
After filing a claim, policyholders want visibility: Where is my claim? When will payment be issued? These inquiries generate significant inbound volume.
Returning to the earlier example, weeks after the accident, the policyholder calls for an update. Repairs are ongoing, rental coverage is nearing its limit, and payment timing will determine next steps.
In theory, this is a simple request. In practice, it rarely feels that way.
Limitations of a human-only approach
Agents place callers on hold while accessing multiple systems to locate claim records, review adjudication status, check documentation, and confirm payment details. They must then translate complex insurance terminology into understandable language.
This leads to:
- Delayed access to information: Multiple systems and credentials slow retrieval, driving longer hold times during high call volumes.
- Communication gaps: Concepts such as deductibles, depreciation, and adjudication stages are difficult to explain clearly, often prompting repeat calls.
- High callback volume: Without proactive updates, policyholders call frequently for status checks, consuming agent capacity with repetitive inquiries.
How AI agents improve claims status interactions
An AI agent can instantly verify identity, retrieve claim information, and explain status updates in plain language. It highlights outstanding requirements, provides estimated timelines, and offers proactive notifications via SMS or email, significantly reducing inbound calls.
Business impact:
- Immediate, self-service access to claim status
- Clear explanations that reduce repeat inquiries
- After-hours availability without extending agent shifts
Delivering speed when trust is on the line
Insurance is built on trust, and contact centers are where that trust is tested. Policyholders expect clarity, responsiveness, and reliability during moments that matter most.
AI agents are designed for high-volume, procedurally driven interactions: FNOL intake, claims status inquiries, billing questions, and policy updates. This allows human agents to focus on work that requires judgment and empathy, including complex claims, fraud investigations, coverage disputes, and sensitive conversations.
Cresta AI Agent delivers human-like conversations across channels while protecting your brand, data, and compliance requirements. Insurers no longer have to choose between operational efficiency and exceptional customer experience.
With Cresta AI Agent, customer interactions are connected across channels on a single platform built for both people and AI—helping teams automate more, maintain quality, and respond with confidence when it matters most.
Learn more about Cresta AI Agent capabilities and connect with our team for a personalized demo.
