Insurance Analytics Consulting

Frequently asked questions

Insurance data work that holds up under regulatory scrutiny.

Why insurance data projects stall.

What insurance clients ask before they engage.

Often paired with insurance engagements.

Ready to fix your insurance data layer?

Five departments, five different versions of the same problem.

Core operations (claims)

Finance and accounting

Customer service (policy servicing)

Shared services (underwriting intake)

IT and transformation

How do you handle data from multiple legacy policy administration systems?

We build a unified data layer that normalizes and reconciles data from multiple source systems without requiring a platform replacement. We map each source to a common semantic model and document the lineage so every number is traceable to its origin.

Yes. We build automated pipelines that produce regulatory outputs directly from your certified data layer. This eliminates the manual reconciliation that typically consumes weeks of actuarial and finance team time before each filing cycle.

Most insurance data foundation engagements run 12 to 16 weeks. We start with a 30-day Analytics Truth Audit that maps your current data landscape and identifies the highest-priority gaps before any build work begins.

We work with both. The data structures differ significantly between lines of business, but the underlying governance and metric layer challenges are consistent. We've experience with personal lines, commercial lines, specialty, and health insurance data environments.

Insurance data analytics consulting for P&C, life, and health carriers. Unify claims data, automate regulatory reporting, and build trusted metrics.

Data analytics for insurance carriers and MGAs. Claims, underwriting, and risk metrics.

Insurance companies sit on decades of claims, underwriting, and policyholder data that's rarely unified or governed. We build the metric layer that makes regulatory reporting, loss ratio analysis, and AI-driven underwriting possible.

Insurance data work that holds up under regulatory scrutiny.

Start with a 30-day Analytics Truth Audit. We identify exactly what is broken and give you a 90-day roadmap to fix it.

Core operations (claims), owned by VP Claims, Claims Operations Director, COO.

Adjusters spend most of their day reading documents, not adjusting.

FNOL, document review, coverage check, routing, and adjudication are manual; roughly 80% of claim time is document handling.

Straight-through processing for standard claims: agent extracts from FNOL and supporting documents, checks coverage, scores complexity, routes; adjusters receive only the 15 to 20% needing judgment, with every decision logged.

Measured on Claim cycle time, straight-through rate, loss adjustment expense per claim.

The work behind it: AI agents and workflow automation, Document processing, Human-in-the-loop operations design, Agent evaluation and QA, Workflow and system integration, Proof of concept.

64% of insurers name claims top AI priority; 86% raising AI spend in 2026 (Accenture); 65% plan scaled claims agents in 2026 (Roots AI).

Finance and accounting, owned by CFO, Controller, Head of Premium Accounting.

Commission and bordereaux reconciliation lives in one person's spreadsheet.

Premium billing, broker commissions, and reinsurance recoveries reconciled by hand each month from PDFs and portals.

Process mining shows the rework; agent ingests statements and bordereaux, matches to policy and premium records, raises exceptions to finance with the evidence attached.

Measured on Reconciliation hours per month, unapplied cash, recoveries collected.

The work behind it: AI agents and workflow automation, Process mining, Document processing, Workflow and system integration.

Claims and premium operations are the top two insurance AI investment areas in 2026 industry surveys.

Customer service (policy servicing), owned by Head of Customer Service, VP Policy Operations.

We answer the same certificate and status requests all day.

Endorsements, certificates of insurance, claim status, and renewals handled by CSRs working the policy system by hand.

Agent issues certificates and status updates in the carrier's templates, processes simple endorsements, escalates any change that affects coverage or premium; fine tuning only for document format.

Measured on Requests resolved without a CSR, certificate turnaround, renewal retention.

The work behind it: AI agents and workflow automation, Human-in-the-loop operations design, Agent evaluation and QA, Fine tuning.

71% of claims professionals say AI can reduce administrative delays, 60% expect faster resolution (Wisedocs 2026).

Shared services (underwriting intake), owned by Chief Underwriting Officer, Head of Underwriting Operations.

Submissions sit in a shared inbox and good risks go stale.

Broker emails triaged manually, data rekeyed into the rating system, incomplete submissions bounced days later.

Agent reads submissions, extracts ACORD and loss-run data, checks completeness and appetite, assigns to the right underwriter same day, bounces incomplete ones automatically with a list of what is missing.

Measured on Submission to quote time, quote ratio, underwriter capacity.

The work behind it: AI agents and workflow automation, Document processing, Human-in-the-loop operations design, Workflow and system integration.

Submission triage and pre-bind document checks named as specific 2026 agent deployments (AI for Insurance 2026 guide).

IT and transformation, owned by CIO, Head of Policy Systems.

Nothing talks to the policy admin system.

Guidewire, Duck Creek, or the AMS has no clean write-back path, so automation lives outside it and someone rekeys.

Agent actions written to the policy system with full audit; evaluation evidence packaged for NAIC model bulletin and state regulator review.

Measured on Rekeying hours eliminated, regulator findings, time to approve new automation.

The work behind it: Workflow and system integration, Agent evaluation and QA, AI agents and workflow automation.

Insurance AI expected to be classified high risk under the EU AI Act; NAIC AI model bulletin adopted by most US states.