05 · Simulated output

Challenge the AI output

ClaimReview AI produced the outputs below. They are fictional and deliberately imperfect. An output is not evidence that the result is valid.

More fraud found is not the same as fair treatment.

410 of the 500 resolved SIU referrals, 82%, were genuine. Ask who is being referred, how long they wait, and what they are told.

Fraud scores and routing
Case	Fraud score	Routing decision	Simulated AI rationale	What later emerged
Claimant ARetired customer, storm damage	82	Referred to SIU	Claim soon after a cover increase; claim value in top decile.	Genuine. Held seven weeks with no explanation.
Claimant BYoung driver, minor collision	74	Referred to SIU	Short policy tenure and out-of-hours submission.	Genuine. Cleared after 15 working days.
Claimant CTenant in a high-deprivation area	77	Referred to SIU	High postcode risk index and a prior claim.	Genuine. Cleared after 26 working days.
Claimant DStaged accident ring	96	Referred to SIU	Linked parties and new policies.	Fraud. Correctly detected, saving £84,000.
Claimant ECustomer with English as a second language	79	Referred to SIU	High call-transcript inconsistency score.	Genuine. The 'inconsistencies' were transcription errors.

Your assessment

Do you trust these outputs? Why or why not?

I would not rely on these outputs without… / I would investigate first…

Patterns across the cases

What do the errors have in common? What could be causing them?

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