How AI Agents Can Automate Insurance Claims Processing?

Introduction

Poor claims experiences could put up to $170 billion in global insurance premiums at risk over five years, according to a third-party Accenture study of 6,754 policyholders and 128 claims executives. The same research found that 31% of claimants were not fully satisfied with their claim, and 60% of those unhappy customers pointed to slow settlement. Almost one in three of them switched insurers.

Claims are the moment of truth for an insurer. A policyholder who has just had an accident or a burst pipe wants a fast answer, not a hold queue. Yet most claims teams still rely on phone calls, email threads, and manual data entry to move each file forward.

Automated insurance claims fix this by handing the repetitive work to software. This guide explains what insurance claims automation is, how the process works, and how AI voice agents (software that talks with callers in natural speech and completes tasks for them) can run the phone side of claims. You will also see the features to look for, the benefits, and how Level AI fits in.

What Is Insurance Claims Automation?

Insurance claims automation is the use of software to carry out the steps of a claim with little or no manual work. It covers intake, data capture, document collection, status updates, routing, and follow-up. A person steps in only when a claim needs judgment, such as a coverage dispute or a large loss.

You will also see this called claims processing automation, automated claims management, or insurance claim process automation. The idea is the same. The software does the repeatable tasks, and your team handles the exceptions.

Claims automation has three layers:

1. Rules-based automation. Fixed "if this, then that" logic routes a claim or flags a missing field.

2. Document and data tools. Software reads forms, photos, and PDFs and pulls the data into your claims system.

3. AI agents. These handle live conversations by phone, chat, or text, decide the next step, and update your systems on their own.

The third layer is where most of the new gains are. A large share of claims work is conversation: a customer reporting a loss, asking where their claim stands, or sending a missing document. AI agents for insurance claims take over those conversations.

How Does Insurance Claims Automation Work?

Automated insurance claims processing follows the same path a manual claim does. Each step is handed to software instead of a person. Here is the usual flow:

1. Intake. The customer reports the loss through a call, a chat, an app, or a web form. The system records who they are, what happened, and when.

2. Verification. The software confirms the caller's identity and checks that the policy is active and covers the type of loss.

3. Data capture. Details such as date, location, parties involved, photos, and police reports are collected and stored in structured fields.

4. Triage and routing. Simple claims go down a fast path. Larger or unusual claims, including those with fraud signals, go to an adjuster.

5. Assessment and decision. Rules and models review the data. Straight-through processing, meaning a claim is approved and paid with no human touch, applies to the simplest claims. Everything else goes to a person with a complete file.

6. Updates and follow-up. The customer gets status updates and requests for missing documents without having to call in.

7. Payment and closure. Payment is issued, the file is closed, and the system records the outcome.

8. Quality and compliance review. Conversations and decisions are checked against your rules and state requirements.

The table below shows what changes when each step is automated.

Quality review is the step many teams forget. Most insurance contact centers sample only a small slice of calls, which leaves most conversations unchecked. Automated scoring closes that gap, and it matters even more once AI starts handling calls.

How Do You Automate Insurance Claims Using AI Voice Agents?

Calls are still how many policyholders report a loss and chase an update. An AI voice agent that can hold a real conversation turns that phone line into an automated insurance claims channel. Older phone menus, also called IVR, force callers to press numbers and often fail on anything outside the menu. An AI voice agent lets the caller simply explain what happened.

Here is how to set it up, step by step.

1. Pick the claims calls to automate first. Start with high-volume, rule-based calls. Good first picks are first notice of loss (FNOL, the first report a policyholder makes after a loss), claim status checks, and requests for missing documents. Leave complex disputes with your adjusters.

2. Map the conversation and the rules. Write down what the agent must ask, what it may say, and when it must hand off. For FNOL, that means the questions your adjusters ask today, in the same order. Rules for authentication, coverage questions, and sensitive cases should be fixed, not left to chance.

3. Connect the agent to your systems. The agent needs to look up the policy and claim and write data back. Without these connections, it can only talk. With them, it can finish the task. Check the list of supported system connections for your CRM, claims platform, and phone system.

4. Build in a clean handoff to people. Some calls should go to a person, such as an injury claim or an upset customer. The agent should pass over the caller's identity, the claim details, and a summary so the customer never repeats the story. Level AI's context handoff is built for this.

5. Add outbound calls. Claims need follow-up: a missing photo, an appointment with a repair shop, a payment confirmation. AI agents can place these calls at scale. Level AI's guide to proactive outbound calling with virtual agents covers how this works.

6. Pilot, measure, and expand. Launch on one claim type or one line of business. Track how many calls the agent completes without help, how many are handed off, and how accurate the answers are. Then widen the scope.

What an AI voice agent does on a claims call

Here is a simple FNOL example:

1. A policyholder calls after a car accident, and the agent answers right away.

2. The agent confirms identity with details such as a date of birth or policy number.

3. It checks that the policy is active and pulls up the coverage.

4. It asks about the accident: when, where, who was involved, and whether anyone was hurt. If there are injuries, it routes to a person right away.

5. It creates the claim record, assigns a claim number, and tells the caller what happens next.

6. It texts a link so the caller can upload photos, then follows up if they are not received.

This pattern already works in other regulated industries. A global healthcare provider uses a Level AI voice agent that verifies the caller, retrieves records from its systems, writes structured data back, and hands off out-of-scope calls. In early results, the agent handled 45% of prescription refill calls without a human agent. A contact center leader at the provider said, "I think you've proven in my eyes that you're able to deliver on what you say you can deliver on." That is a prescription workflow, not an insurance claim, but the steps are the same: verify, look up, act, write back, and escalate when needed.

Ready to see an AI agent handle claims calls? Book a walkthrough of Level AI's virtual agent with your own claims scenarios.

What Are the Key Features of Claims Automation Software?

Not every tool that says it automates claims does the same job. Use the list below to compare options. The table after it shows why each feature matters.

1. Natural voice conversations. The agent should handle interruptions, accents, and unclear answers. Speech recognition quality sets the ceiling, so ask how it performs on noisy, real calls. Level AI's speech recognition technology is built for contact center audio.

2. Connections to your claims systems. The agent must read and write to your claims platform, CRM, and phone system.

3. Fixed workflows plus flexible conversation. Rules should control authentication and policy language. The conversation around them should still feel natural.

4. Human handoff with context. A smooth transfer protects both the customer and the adjuster's time.

5. Built-in compliance controls. Claims calls carry disclosure scripts, privacy duties, and state rules. Your software should enforce them, not rely on memory.

6. Multilingual support. Policyholders should be able to report a claim in their own language.

7. Quality scoring on every AI conversation. You need proof that the agent gave correct answers, not just that the call ended.

8. Reporting and audit trails. Every decision should be traceable for regulators and internal reviews.

Compliance. Claims-handling rules differ by state, and calls often involve personal and health data. Look for vendors that publish how they handle data. Level AI's guide to voice AI privacy, security, and compliance lists the questions to ask, and its regulatory compliance monitoring checks conversations against your own rules.

Language coverage. If your policyholders speak more than one language, a single-language agent leaves gaps. A multilingual AI agent lets you offer the same claims service in every language you support.

What Are the Benefits of Insurance Claims Automation Using AI Voice Agents?

Automated claims management with voice agents pays off in six areas.

1. Faster first response. The agent answers on the first ring, day or night. Slow settlement is the top complaint in the Accenture research above, and the first call sets the pace for the whole claim.

2. Handling surges. A storm or a flood can multiply call volume overnight. AI agents take the surge without a hiring scramble. See how AI agents handle call surges without hold queues.

3. Lower cost per claim. Each call the agent completes is a call a person does not have to take. One customer, Uown Leasing, had a Level AI virtual agent handle over 30% of its inbound calls and reported a 3 to 4x financial return compared with hiring agents. It is a collections use case in financial services, not insurance, but the cost logic carries over. Daniel Klein, its CEO, described what came before as hours when "the consumer would reach an IVR, leave a voicemail if they chose to." Read the full Uown Leasing case study.

4. Cleaner data. The agent captures details in the same structured fields every time. Adjusters get complete files and spend less time chasing missing facts.

5. Better use of adjusters. When routine calls are automated, your experienced staff work on complex and sensitive claims. A Level AI insurance provider case study showed average handle time down 20% and first call resolution up 15% after adding AI support for human agents.

6. Consistent compliance. The agent says the required words every time. When every AI call is also scored, you can show regulators your evidence. A head of conversational AI at a global reinsurance leader said quality managers can "save up to 50% of their time" when scoring is automated and based on risk.

Automation also has limits. An agent that completes a call is not always an agent that gave the right answer. A high completion rate can hide wrong answers, so check accuracy as well as volume. Level AI's article on failures hidden inside AI agent containment numbers explains what to measure.

How Can You Use Level AI to Automate Insurance Claims?

Level AI is a platform for customer conversations. It combines AI agents that handle calls with automated quality scoring, real-time agent support, and analytics. For insurers, that means the agent that takes the call and the system that checks it work from the same data.

Here is how it maps to the claims journey:

1. Take the call. Level AI's AI agents handle high-volume policyholder requests by voice and chat, including FNOL submissions, policy questions, and billing questions. They can be prepared in advance for predictable surges, such as storm season.

2. Follow your rules. One builder combines fixed workflows (for authentication and policy language) with natural conversation, so the agent follows your process.

3. Hand off cleanly. Complex claims move to a person with identity, claim details, and a call summary attached.

4. Score every conversation. Every virtual agent conversation is scored against the same rubrics used for human agents, covering accuracy, resolution quality, and compliance. Level AI's automated quality assurance applies the same standard to AI and human calls.

5. Spot trends early. Claims status complaints, payment gaps, and denial disputes show up in the conversation data before they become formal complaints.

6. Support your adjusters. Real-time guidance helps human agents follow disclosure rules and next steps on live claims calls.

You can see how these pieces come together on the Level AI page for insurance. If you are comparing vendors, start with this list of the best AI voice agents for enterprise insurance and the guide on how to evaluate AI voice agent platforms.

Want to see FNOL and claim status automation on your own call flows? Schedule a demo and our team will walk you through it.

How Level AI Helps You Run Automated Insurance Claims

Claims decide whether a policyholder stays or leaves. Most of that experience is built in conversations: the first report, the status check, the missing document, the payment question. Automated insurance claims put software on the repetitive part of those conversations and give your people room to handle the claims that need care.

Level AI gives insurance teams a way to do this without losing control. Its AI agents take claims calls and follow your rules. Its quality and compliance tools score each conversation, whether a person or an AI handled it. Start with one claim type, measure accuracy and handoff quality, and expand from there.

Cut claims wait times without adding headcount.

Level AI's AI agents answer FNOL and claim status calls around the clock, follow your workflows, and hand complex claims to your team with full context. Every conversation is scored, so you can trust what the AI says on your behalf

Schedule a demo

Cut claims wait times without adding headcount.

Level AI's AI agents answer FNOL and claim status calls around the clock, follow your workflows, and hand complex claims to your team with full context. Every conversation is scored, so you can trust what the AI says on your behalf

Schedule a demo