Build a Data Strategy for Property & Casualty Insurance

Data is fragmented across policy, claims, actuarial, and financial systems, limiting trust and usability.
Inconsistent definitions and unclear ownership weaken pricing, reserving, reporting, and model governance.
Manual reconciliation slows analysis and increases operational risk.
Regulatory expectations demand stronger transparency, explainability, and documentation.

Our Advice

Critical Insight

Reliable and well-governed data strengthens pricing, claims accuracy, reserving confidence, and audit readiness, creating a real competitive advantage for P&C insurers.

Impact and Result

Improved data quality, consistency, and integration across underwriting, claims, and actuarial workflows.
Faster, more reliable risk and loss insights to support pricing and reserving decisions.
Stronger regulatory compliance, audit readiness, and measurable business value from data investments.

Build a Data Strategy for Property & Casualty Insurance Research & Tools

1. Build a Data Strategy for Property & Casualty Insurance Storyboard – Empowers P&C insurers to turn fragmented data into trusted, governed insight that strengthens underwriting, claims performance, and regulatory confidence.

This storyboard delivers a clear, actionable path to data maturity for P&C insurers, helping leaders assess readiness, establish governance and ownership, and embed data discipline into underwriting, claims, and actuarial workflows to unlock measurable business value.

2. Data Strategy Accelerator Tool – Helps P&C insurers validate, operationalize, and scale data governance by confirming it works in real underwriting, claims, and actuarial workflows.

This deliverable provides a guided, scenario-based assessment of data readiness across underwriting, claims, actuarial, and regulatory functions. It calculates maturity scores, highlights critical data risks, and supports the design of clear ownership, definitions, and controls, enabling insurers to focus remediation efforts where they will deliver the greatest business and compliance impact.

3. Data Governance Adoption Assessment – Helps P&C insurers validate, operationalize, and scale data governance by confirming it works in real underwriting, claims, and actuarial workflows.

This template assesses whether the data governance model defined in earlier phases can be successfully adopted in day-to-day insurance operations. It validates roles, definitions, and controls in practice; confirms data quality improvements translate into measurable business outcomes; and determines readiness to scale governance across the enterprise.

4. Data Strategy Execution Roadmap Tool – Helps P&C insurers prioritize, sequence, and derisk data initiatives to turn data strategy into a clear, executable roadmap.

Turn fragmented insurance data into reliable, actionable insights.

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We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.

What Is a Blueprint?

A blueprint is designed to be a roadmap, containing a methodology and the tools and templates you need to solve your IT problems.

Each blueprint can be accompanied by a Guided Implementation that provides you access to our world-class analysts to help you get through the project.

Need Extra Help?
Speak With An Analyst

Get the help you need in this 4-phase advisory process. You'll receive 8 touchpoints with our researchers, all included in your membership.

Guided Implementation 1: Assess the P&C Data Landscape and Readiness

Call 1: Align on goals, scope, and current data challenges.
Call 2: Review data flows, inconsistencies, and business impacts.

Guided Implementation 2: Design the P&C Data Governance Framework

Call 1: Define ownership, stewardship roles, and shared definitions.
Call 2: Establish governance controls, workflows, and decision paths.

Guided Implementation 3: Pilot and Validate the Governance Model

Call 1: Select the pilot workflow and train users on definitions and rules.
Call 2: Measure pilot outcomes and refine the governance model.

Guided Implementation 4: Build the Data Readiness Action Plan and Roadmap

Call 1: Prioritize improvements and build the 90-day action plan.
Call 2: Finalize the execution roadmap and confirm next steps.

Author

Vidhi Trivedi

Contributors

Fahad Shaikh, Data & AI Advisor, Previously at Aviva
Amanda Evenson, Vice President, Data & Analytics, Red River Mutual