Artificial Intelligence in Claim Investigation and Expertise Support

Gains:

• Ability to summarize damage notification, expert report and document pile with artificial intelligence and mark deficiencies and inconsistencies
• Ability to cross-validate the artificial intelligence output with the policy text in the evaluation of coverage, exclusion and exemption
• Understanding that damage payment, partial payment and rejection decisions require competent damage adjuster and compliance approval.

The promise that insurance makes to the customer reaches its true moment in the payment of claims. When a claim occurs; to receive the notice, collect the documents, have an appraisal (an independent expert determine the reality and amount of the damage), evaluate the policy scope and decide on payment/partial payment/rejection. In this process, the damage adjuster and the damage specialist read many documents (notice form, expert report, invoice, photo, minutes, policy text) together. Artificial intelligence (software that summarizes documents and flags inconsistencies) alleviates this document burden: summarizes the file chronologically, lists missing documents, catches discrepancies in the expert report. But the coverage and payment decisions depend on the wording of the policy and the responsibility of the expert; AI cannot undertake this. In this unit, you will learn how to safely review the claim file with artificial intelligence, how to cross-verify the coverage decision with the policy, and why the payment/rejection decision remains with the human.

What does artificial intelligence do in the damage file

A claims file is usually messy and multi-documented. Artificial intelligence speeds up:

• Chronological summary: Arranging the events in time order, from the date of notification to the expertise, from document delivery to correspondence.
• Missing document detection: Listing which required documents (reports, invoice, expert report, license) are missing according to the policy type.
• Inconsistency marking: To detect the contradiction between the incident description in the notification form and the findings in the expert report (for example, traces of damage occurred while moving on a vehicle called "crashed while parked").
• Document summary: Extracting a long appraisal report, item by item, with damage items and amounts.

What AI does not do is make coverage and payment decisions. The sentence "This damage is covered" or "must be paid" is a legal-technical decision depending on the special and general conditions of the policy, exclusions (situations excluded from coverage) and exemptions (amount borne by the insured).

Attention: Even if the artificial intelligence says "it is covered", this is a preliminary evaluation. The coverage decision is made by the competent loss adjuster by confirming line by line with the special and general conditions of the policy.

Cross-verify coverage decision with policy

Coverage is determined by three layers and each must be checked:

1. Is there any guarantee? Is this risk covered in the policy? (For example, flood coverage may be an additional coverage in the automobile insurance policy; it may not be in the standard package.)
2. Are exceptions applied? Is there a clause in the general conditions of the policy that excludes this event from coverage? (For example, wear, lack of maintenance, intentionality.)
3. What are the exemptions and limits? How do the deductible amount and coverage limit assumed by the insured affect the damage amount?

AI can sketch these three layers; But each layer must be confirmed from the policy text. Although general conditions are standard, special conditions vary from policy to policy and take precedence.

Tip: Include the policy text in the prompt and say, "Write which clause/condition clause is based on each coverage claim." Thus, the output becomes controllable and the hallucination (fabricated substance) becomes immediately visible.

Step by step: AI-assisted damage inspection

1. Anonymize context. Remove insured name, ID number, policy number, license plate and health information.
2. Summarize the file chronologically. Extract the event flow and document delivery order.
3. Have the omissions and inconsistencies listed. Mark missing documents and discrepancies between documents according to policy type.
4. Ask for a scope outline — not a decision. Draft the coverage/exception/exemption points with reference to the policy article.
5. Confirm line by line with the policy. Verify each scope claim against specific and general terms.
6. Calculate the damage amount independently. Calculate the net payment yourself by applying the exemption and limit.
7. Write down the decision and its reasoning. Record the payment/partial payment/rejection decision, indicating the basis on which it is based; Obtain compliance/legal approval if necessary.

three mini cases

Case 1 — Catching the fabricated substance. In a residential water damage file, artificial intelligence said, "According to Article 8 of the General Conditions, water damage caused by plumbing is covered by warranty." The claims expert opened the policy: the relevant item number was different and there was a special exemption for plumbing water in this policy. The artificial intelligence made up the article number and skipped the special condition. The expert reassessed the coverage with the correct clause and deductible.

Case 2 — Making the inconsistency visible. In a traffic accident file, the notification form stated "speed 40 km/h"; The findings of deformation and brake marks in the expert report indicated a much higher speed. Artificial intelligence juxtaposed this contradiction. The expert initiated additional investigation; this was critical for both accurate compensation and suspicion of possible fraud.

Case 3 — Applying the exemption correctly. The repair bill for a motor vehicle damage was 118,000 TL, and the policy had a 2% exemption (18,000 TL over the vehicle price of 900,000 TL). Artificial intelligence summarized the net payment as 118,000 TL; He had forgotten the exemption. The expert corrected the net payment as 100,000 TL by independent calculation. The independent account protected both the company and the insured with the correct amount.

Four copyable prompts

1) Chronological file summary:

You are a damage adjuster's assistant. Summarize the following anonymized claims file in date order: [paste documents]Output: sequence of events (dated), documents delivered, key findings. Write which document you rely on for each item. DON'T decide on coverage or payment.

2) Missing documents and discrepancy scanner:

In the following [policy type] claim file:1. List the missing documents required for this policy type.2. Mark the contradictions between the documents (event narrative vs. expert finding, date, amount, address) by showing them side by side.File: [paste]. Add a comment; only deficiencies and contradictions are removed.

3) Scope assessment draft (not decision):

Below is the anonymized damage summary and the special + general conditions of the policy. Damage: [paste] Policy terms: [paste] Task: Evaluation in terms of coverage / exception / exemption. Create a DRAFT. Quote the article number you rely on at each point verbatim. Don't make up the item you are not sure about; Write "conditions not found". I will make the final coverage decision.

4) Net payment account control:

Calculate the net payment step by step with the following damage amount, deductible and limit information:Repair/damage amount: [x]Deductible: [rate/amount] Coverage limit: [y]Insurance amount/underinsurance status: [z]Show each step. I will check the result independently.

Weak prompt / Strong prompt

Weak: "Examine this damage file, tell me if it should be paid."

Problem: Direct coverage/payment decision (red zone) requested; There is no policy text and no article reference. The model fits scope and substance.

Güçlü: "Act as a loss adjuster's assistant; summarize this anonymized file chronologically, mark omissions and inconsistencies, draft coverage points with reference to the policy article. Make a coverage/payment decision."

Why it's good: The task is in the yellow zone, the output is document and article referenced, the decision remains with the expert.

comparison chart

Quest

artificial intelligence

Damage adjuster

verification source

Chronological summary

draft

Reads, confirms

Documents

Missing document detection

List

Evaluates

Policy/procedure

Inconsistency marking

signs

examines

interdocumentary

Scope assessment

draft

decides

Special + general conditions

Net payment account

draft account

Independent accounts

Exemption/limit

Payment/rejection decision

—

Decision + signature

Policy + compliance/legal

Common mistakes

• Accepting the scope claim without substance confirmation. Artificial intelligence can make up item number and content; always verify from the policy.
• Skipping special terms. General conditions are standard, but special conditions take precedence and are specific to the policy.
• Forgetting exemptions and limits. Calculating net payment without exemption produces an incorrect amount.
• Ignoring inconsistency. Omitting the contradiction between the incident narrative and the expert finding creates the risk of both incorrect payment and fraud.
• Copying the rejection reason from artificial intelligence. Rejection has legal consequences; The justification must be based on the policy article and must be written by an expert.

In summary

In damage inspection, artificial intelligence summarizes the file chronologically, lists missing documents and flags inconsistencies; but does not decide on coverage and payment. Confirm coverage line by line with policy text at three layers (coverage/exclusion/exemption); independently calculate the net payment with deductibles and limits; Make the payment/partial payment/rejection decision as a competent loss adjuster, with compliance/legal approval when necessary. The final decision belongs to the human.

Application task

Get a damage file (anonymized) for testing purposes. Create a chronological summary and list of inconsistencies with prompts 1 and 2. Then, request a coverage draft at prompt number 3 and check item by item whether each coverage claim actually exists in the policy. How many of the claims had real material basis, and how many were fabricated/false? Note the result.

checklist

• [ ] I anonymized the file context.
• [ ] I made a chronological summary and a list of missing documents.
• [ ] I marked inconsistencies between documents.
• [ ] I confirmed each coverage claim with the policy item number.
• [ ] I checked the special terms before the general terms.
• [ ] I calculated the net payment independently with deductible and limit.
• [ ] I recorded the reason for the payment/rejection decision; I received the necessary approval.