Sovereign claims and underwriting explainability engine
Adjudicator is an explainability layer for AI-assisted claims and underwriting. It does not replace the insurer’s models; it makes their decisions defensible, producing a plain-language rationale for every outcome and testing for the fairness that TCF and the FSCA require.
A sample claim, assessed the way Adjudicator would: a decision, a plain-language rationale, and a fairness check, so the outcome is defensible to the FSCA. An illustration of the workflow, not a live policy.
Plain-language rationale
The death occurred in policy month 5, inside the 6-month waiting period for natural causes. Premiums were fully paid, so this is a waiting-period outcome, not a lapse. The customer is due a full refund of premiums.
Decision + rationale retained for the FSCA
Under the Solvency Assessment and Management regime, FSCA conduct standards, and Treating Customers Fairly, an automated decision that cannot be explained or shown to be fair is a regulatory liability. Foreign black-box models fail this on both counts. Adjudicator sits over the decision pipeline on sovereign infrastructure and turns every output into something an insurer can stand behind.
Adjudicator wraps the existing claims or underwriting model, capturing inputs and outputs.
It generates a plain-language rationale a customer and a regulator can both follow.
Outcomes are checked for fairness across cohorts; outliers are routed to human review.
The full rationale and fairness record is retained for an FSCA enquiry.
Regulatory frame
Adjudicator is being built with design partners. If this is your problem, help shape it.
