WHERE AGENTIC AI BREAKS HERE
Vulnerable-customer signals missed
Agentic AI optimised for throughput reads the claim and misses the cues that should trigger a careful human touch.
Prompt injection through claimant free text
Claim narratives and supporting statements are injection surfaces. Nudged agentic AI drifts toward a non-policy settlement.
Hallucinated policy-coverage interpretations
On edge-case claims, the agent invents coverage logic that reads as authoritative but does not match the policy wording.
Agentic AI triages the claim and recommends a settlement
Claim documentation, policy wording, claimant narrative, and prior history all read inside the autonomous loop.
Disseqt scores it for consumer duty, consistency, and vulnerable-customer signals
Every recommendation checked against fairly thresholds and decision history across comparable claims.
Claims handler sees confidence score and root-cause analysis on flags
The handler reads what triggered the flag, the policy context, and the specific case that needs human override.
Consumer-duty-ready evidence pack generated per workflow run
FCA, state-insurance, and EU AI Act artefacts assembled from live decisions, ready for conduct review on demand.
Per-claim consumer-duty scoring
Every settlement evaluated against consumer-duty and vulnerable-customer thresholds before it reaches the claimant.
Consistent settlement logic across the book
Aggregate decision patterns surfaced before they become a fair treatment threshold investigation
Consumer-duty-ready evidence pack
FCA, state-insurance, and EU AI Act artefacts generated from live decisions, ready to hand to a regulator.
One pattern, adjacent workflows
The same assurance shape reused across claims, complaints, and policyholder communication agents.
