Underwriting and claims
that can be defended later.
Evidence. Counter-evidence. Human authority. Decision record.
When AI influences underwriting, pricing, claims review or fraud referral, the organisation still needs to know which evidence supported the decision, what could invalidate it, who had authority and what action followed.
Choose one decision
with a real consequence
Risk selection
What evidence supported the classification or recommendation, what was assumed and what finding should overturn it.
Price or terms
Which inputs and rules materially shaped the recommendation and who may accept any resulting change.
Triage and review
When AI prioritises, recommends, routes or materially influences the handling of a claim.
Referral and intervention
When a model or agent moves from detecting a signal to a consequential operational step.
What decision assurance
makes explicit
Decision map
Where the AI enters the workflow and what consequence follows.
Evidence map
The information the recommendation relied on and its provenance.
Counter-evidence
Which findings should suspend, qualify or reverse the recommendation.
Human Authority Matrix
Who may accept, reject, escalate or stop the action.
Action boundary
What may be automated and what remains outside AI authority.
Governed Decision Record
What is preserved so the decision can be examined later.
The initial scope can remain read-only or shadow-first. SINAIGROUP-AI does not underwrite, settle claims, set policy, provide legal opinions or claim regulatory certification.
One workflow.
One accountable owner.
The objective is not to redesign the insurer. It is to take one consequential AI-supported decision and make its evidence, challenge, authority, permitted action and record explicit enough to inspect.
The same control problem
appears in adjacent decisions
Insurance decision assurance
in plain language
What is AI decision assurance in insurance?
It is the examination of the evidence, assumptions, counter-evidence, authority, permitted action and audit record surrounding an AI-supported insurance decision.
Can AI Decision Assurance replace underwriting or claims authority?
No. The organisation keeps its underwriting, claims and business authority. Decision assurance makes the evidence, challenge, authority and action boundary around the AI-supported decision explicit.
What insurance decisions can be reviewed?
Examples include underwriting, pricing, claims triage, claims review, fraud referral and other consequential insurance workflows where AI influences a decision or action.
Bring us one
insurance decision
Tell us where AI influences underwriting, pricing, claims or fraud handling and what happens if the decision is wrong.