Make AI and IP exposure
measurable for underwriting and claims.
We map the chain-of-custody gaps in how your teams use AI, identify the evidence needed to assess data and IP loss, and deliver a practical control plan for underwriters and claims teams.
Led by Sharon L. Bolding, PhD — global AI compliance-surveillance work at Citi · PhD in linguistics.
Where insurance data meets AI risk
Underwriting inputs
Proprietary models, rating logic, and sensitive applicant data enter AI tools with little chain-of-custody.
Claims & evidence
Assessing AI or IP loss requires an evidentiary record most teams don’t yet capture.
Regulatory scrutiny
Decisions that materially affect a policyholder must be explainable, traceable, and auditable.
The AI Data Exposure Assessment
A focused, fixed-scope engagement shaped around your regulatory reality. In eight hours we map your exposure and hand you a plan your team can act on.
Eight hours · fixed scope · fixed fee
- Workflow map — where underwriting/claims data enters AI tools
- Exposure findings — the chain-of-custody gaps that matter most
- Prioritized controls — what to fix, in what order
- 30-day action plan — concrete next steps
Book an AI Data-Risk Assessment
Tell us a little about your organization and we’ll be in touch to schedule.