Solution Brief

The Future of Insurance Runs on Semantics

Semantic Layer for Insurance

What Is a Semantic Layer?

A semantic layer is a business-friendly data model that makes raw data accessible in familiar terms like “premium,” “loss ratio,” or “coverage type.”
AtScale’s Universal Semantic Layer ensures these definitions are consistent across every tool—Excel, Tableau, Power BI, and now, GenAI platforms like Databricks Genie and Snowflake Cortex.

Insurance companies leveraging a semantic layer have achieved:

View PDF Button Arrow

The insurance industry is undergoing rapid digital transformation, shaped by evolving customer expectations, stricter regulatory oversight, and a growing demand for real-time insights. But legacy systems, siloed data, and inconsistent reporting continue to stall progress.

From claims to customer retention to regulatory compliance, data is at the heart of every insurance decision. Yet that data often lives across disconnected policy systems, CRM platforms, telematics feeds, and cloud data warehouses—making it hard to trust, act on, or scale analytics.

A universal semantic layer changes that. AtScale virtualizes access to data, standardizes business definitions like “policyholder” and “claim,” and delivers governed insights to BI tools and AI agents alike. No duplication. No extracts. Just fast, trusted answers.

How Insurance Leaders Use a Semantic Layer

  1. Claims Optimization: Accelerate claims triage, detect fraud, and reduce cycle times by unifying policy, claims, and external data.
  2. Member and PMPM Analytics: Streamline PMPM calculations and member-based insights to improve outcomes and reduce cost of care.
  3. Regulatory Reporting: Automate reconciliations and ensure audit-ready, consistent KPIs across all lines of business.
  4. Customer 360 and Retention: Unify CRM, policy, and interaction data to analyze churn risk and personalize retention strategies.
  5. Operational Efficiency: Enable faster actuarial models and underwriting decisions by reducing dependency on IT and siloed data pipelines.

Challenges Solved by a Semantic Layer

✖️ Fragmented Data – Disparate systems and third-party sources limit visibility.
✔️ AtScale virtualizes data across platforms like Snowflake, Databricks, and BigQuery—no movement needed.

✖️ Manual Data Preparation – Analysts rely on IT for pipelines and logic.
✔️ AtScale simplifies modeling with AI-powered agents, reusable definitions, and composite modeling.

✖️ Inconsistent KPIs – Teams use conflicting logic across tools.
✔️ With centralized metric governance, insurers define once and reuse everywhere—across BI tools and AI workflows.

✖️ Cloud Cost Sprawl – Inefficient queries drive up compute and storage bills.
✔️ AtScale generates optimized queries, uses smart aggregates, and slashes compute spend by up to 70%.

Choosing the Right Semantic Layer Solution

When selecting a semantic layer solution, insurers should consider the following:

  • Live Query Execution: Access real-time insights without extracts or duplication
  • Native Power BI + Excel Support: Built-in DAX, MDX, and cube function compatibility
  • AI & GenAI Ready: Model Context Protocol (MCP) enables semantic-aware natural language querying
  • Composite Modeling: Combine global and regional models to support both enterprise and line-of-business use cases
  • Open Standards: Built on the open-source Semantic Modeling Language (SML) for interoperability and version control

Why Now?

As insurers face growing data complexity and AI adoption, governed semantic models are no longer optional—they’re essential.

With AtScale, you modernize legacy systems, reduce risk, and unlock the full potential of your data—whether it’s for dashboards, decisions, or intelligent agents.

Related Resources

See AtScale in Action

Schedule a Live Demo Today

Book a Demo Button Arrow Button Arrow