Algorithmic risk is now a number the DOI and the reinsurer both want.

Tokto gives the carrier's risk and compliance officer one record that ties every algorithmic decision, every adjuster prompt, and every telematics data flow to a policyholder, a state filing, and a rate plan, ready for the state DOI, the AG, the NAIC, the reinsurer, and the board risk committee.

What you get with Tokto

• Every algorithmic decision scored and recorded against a policyholder, an adjuster, a state filing, and a rate plan.
• A single evidence layer that the DOI, the AG, the NAIC, the reinsurer, and the board risk committee read against the same record.
• Policy enforced at the model: no adjustment outside the rate filing, no SDK telemetry without consent.
• AI risk that is measured by state and line, controlled at the model, and attestable to the board and the reinsurer.

How it works

Tokto turns algorithmic exposure into a managed, evidenced risk. Every pricing model, every telematics SDK, every claim-triage co-pilot becomes a scored record at the moment of decision, tied to the policyholder, the state filing, the rate plan, and the consent captured. The risk function sees exposure by state before the plaintiffs' bar does.

When a verdict in one state seeds nineteen more, when the AG opens a privacy enforcement, when the reinsurer prices AI-decisioning risk, the answer is one query against the system of record. The CRO reports algorithmic risk alongside catastrophe and reserve risk — quantified, controlled, and evidenced.

What goes wrong without it

• Algorithmic risk is never quantified by state. The first number is a 37,000-policyholder verdict.
• Telematics SDKs feed models without consent capture. The control gap is the AG's first enforcement.
• An adjustment runs outside the rate filing. The risk register never caught it.
• The reinsurer asks how AI-decisioning risk is controlled. The CRO cannot evidence it. The treaty reprices.