How to handle compensation claims for service failures with an AI agent

A compensation claim needs three answers: did the failure affect this customer, what does your scheme pay for it, and has it been paid already. The agent can find all three from incident records, the published schedule and payment history, then draft the claim. A person approves every payment, and claims for wider losses go to a specialist.

What is a compensation claim, and who owns it?

Service failures happen: an outage, a missed engineer visit, a delayed transfer, a billing error, a late repair. Customers may claim compensation. In some sectors and markets, set amounts apply automatically for certain failures. Many firms also publish their own commitments, such as a credit for each day a service is down. Beyond those, customers sometimes claim for losses the failure caused them, which needs a fuller assessment.

Operations owns incident records. A customer redress or complaints team owns compensation decisions. Finance owns payment. Compliance owns consistency: similar customers should receive similar outcomes. The agent prepares claims and never pays them, consistent with our guide to the AI support agent that knows when to say no. The narrower question is answered in can an AI agent compensate a customer for a service outage?

What are the steps, and at what depth?

1. Agent, depth 1: identifies the failure the customer describes and the period.
2. Agent, depth 1: checks incident records to confirm a failure affected this customer's service in that period: the outage record, the missed appointment, the delayed payment. Incident records are sealed sources; the customer's account is declared.
3. Agent, depth 1: checks the compensation schedule or published commitment that applies, and the eligibility conditions.
4. Agent, depth 1: checks payment history for compensation already paid for the same failure, including automatic payments.
5. Agent, depth 2: drafts the claim: failure, evidence, schedule entry, amount from the schedule, any prior payment, and the customer's own account of the impact.
6. Agent, depth 3: tells the customer what was found and what happens next, without promising an amount until it is approved.
7. Person, redress handler: approves or adjusts the amount within their authority.
8. Agent, depth 1: routes wider loss claims, such as lost earnings or damaged goods, to the specialist team with the evidence the customer has supplied.
9. Person, finance: pays approved compensation.

Which controls matter, and what evidence does each leave?

Incident record first. A claim without a matching incident is drafted as unconfirmed, not rejected; the handler looks into it. Evidence: the incident reference, or its absence, on each claim.

Schedule amounts, not negotiated ones. Evidence: the schedule entry cited for each amount.

No double payment. Evidence: the payment history check on each claim.

Payment is depth 4, and held. Moving money is outside the support agent's role. Evidence: held verdicts and approvers' names.

No admissions beyond the facts. "The outage affected your area on these dates" is a fact from the record. "It was our negligence" is not the agent's to say. Evidence: scope-gate results.

What should you measure?

• Claims drafted, approved and adjusted, and the size of adjustments.
• Unconfirmed claims where the incident record was missing, and how many proved valid. A high number means incident records are incomplete.
• Double payments caught.
• Time from claim to payment.
• Consistency: different amounts for the same failure type, which should be explainable.

Where does it usually go wrong?

Automatic and claimed compensation overlap. A customer already received an automatic credit and claims again. Check history before drafting.

Incident records are too coarse. An outage logged by region misses customers on the edges, or includes ones who were unaffected. Improve the records rather than relying on the customer's word.

Customer evidence is taken as proof. A receipt for a hotel stay during an outage is external evidence. It supports a wider loss claim but must be assessed by a person.

The customer is asked to prove the outage. The firm's own records should show who was affected. Asking customers for screenshots or timings shifts the burden onto them and slows payment. Use customer evidence only where your records are silent.

Goodwill and redress blur. Compensation for a failure is different from a goodwill gesture made to keep a customer happy. Keep them on separate tracks, both for reporting and for consistency.

Failed payments create a second failure. Where compensation is paid as a credit to an account in arrears, or a refund to a card that has expired, the payment fails. The process in handling payment failures for subscribers should not then chase the customer.

Product faults are treated as service failures. A faulty device is usually a warranty matter; see handling warranty claims with an AI agent and can an AI agent handle warranty claims?

Where Pryme fits

In Pryme, incident records reach the agent as sealed sources and the customer's account as declared, and the draft shows both. Payment sits at depth 4 and is outside the support agent's role, so every amount is a held verdict for a named handler. Every claim and decision is filed for consistency review.