AI Strategy & Advisory for Insurance
Insurers know where AI pays: claims, underwriting, fraud, and servicing. The hard part is sequencing those wins under regulators who are now explicit about AI. The NAIC model bulletin expects a written AI program with governance and vendor oversight, state DOIs are asking pointed questions about adverse decisions, and OSFI holds Canadian carriers to model risk expectations. AI strategy for insurance means choosing initiatives that an actuary can stand behind, an examiner can trace, and a policyholder impact analysis will not sink. We build roadmaps that prove value in weeks while the governance your DOI will eventually ask about is already in place.
AI Strategy & Advisory, built for insurance
We inventory use cases across claims, underwriting, fraud, actuarial, and servicing, scoring each on value, explainability burden, and regulatory exposure.
We align the roadmap to the NAIC bulletin's expectations, so your written AI program, governance, and vendor oversight develop alongside delivery, not after it.
We define where explainability is mandatory, especially anything influencing rating, eligibility, or claim outcomes, and design human accountability into those flows.
We sequence quick wins in servicing and triage first, then expand into underwriting and claims decisioning with controls already proven.
Where it pays off in insurance
Claims triage sequencing
Prioritize where AI routes and fast-tracks clean claims first, cutting cycle time without touching contested decisions.
Underwriting decision support
Plan AI that assembles risk evidence for underwriters while keeping the human decision and its rationale on record.
Fraud detection roadmap
Sequence fraud models so investigators get better referrals early, with false-positive monitoring built into the plan.
Actuarial acceleration
Identify where AI speeds data prep and analysis while staying inside actuarial standards of practice.
Carriers commonly cut claims cycle time 30 to 50% on straight-through segments in the first phase, with an AI governance program that satisfies the NAIC bulletin before the DOI asks for it.
Insurance AI, answered
Insurance decisions are rate-regulated and adverse outcomes are examinable. We score every use case on explainability and regulatory exposure up front, so the roadmap favors initiatives an examiner can trace and defers anything that cannot yet be explained to a policyholder.
No, but you need one before scaling, and the NAIC model bulletin effectively requires it. We build the written program, inventory, and vendor oversight in parallel with your first delivery, so governance never becomes the bottleneck.
Anything touching pricing or reserving is planned with your actuaries against applicable standards of practice, and Canadian operations map to OSFI's model risk expectations. The roadmap names the validation evidence each regulator will want.
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