WTW and Databricks Collaborate to Transform Insurance Analytics With Radar Connector

Willis Towers Watson (WTW), a global leader in risk advisory and insurance technology, has taken a significant step forward in insurance analytics by launching the Radar Connector for Databricks — a native integration between its market-leading Radar insurance analytics platform and the Databricks Data Intelligence Platform. The new connector aims to streamline data workflows, enhance governance, and unlock advanced analytics and machine learning capabilities for insurers operating in a data-intensive and highly regulated industry.

The collaboration marries Radar’s powerful pricing, underwriting, and analytics tools with Databricks’ unified data platform, enabling insurers to easily manage, analyse and circulate data without burdensome manual processes. This development is part of a broader trend in insurance technology (insurtech) where firms are breaking down data silos, accelerating analytics performance, and embracing AI-driven insights to improve competitiveness and risk management.

What the Radar Connector for Databricks Does

At its core, the Radar Connector for Databricks enables a two-way data workflow between WTW’s Radar platform and the Databricks ecosystem. Under the new architecture:

• Radar can select Databricks as a native data source, allowing it to pull structured and unstructured data directly from the Databricks Data Intelligence Platform.
• After analysis, results can be written back into Databricks — enabling enterprise-wide sharing, visualisation, and further exploration through Databricks tools.
• Importantly, these processes can be automated within business workflows, eliminating manual steps and reducing data latency from hours or days to minutes.

By eliminating the need for manual data transfers, insurers can achieve significant efficiency gains, improve data governance, and accelerate decision-making cycles — critical advantages in areas like pricing, risk selection, claims forecasting, and portfolio management.

Why This Matters for Insurers

The insurance industry sits atop vast amounts of data — from policy details and claims histories to external sources such as weather data and economic indicators. Transforming this data into actionable insight has always been difficult because:

• Data often resides in disparate systems that lack interoperability.
• Manual data movement is time-consuming, error-prone, and hard to govern.
• Advanced analytics, including machine learning, require unified, governed data sets to function effectively.

WTW’s integration with Databricks tackles these barriers by enabling insurers to unify data — whether structured or unstructured — into a governed environment ready for analytics and AI models. Databricks’ Unity Catalog provides enterprise-grade governance, quality management, and lineage tracking, while Radar’s pricing and analytics modules deliver domain-specific insight tailored to insurance workflows.

With this integration:

• Actuaries and pricing analysts can access up-to-date data faster, with reduced turnaround time for data refreshes and model recalibration.
• Data scientists can combine Radar’s outputs with Databricks machine learning models, enabling predictive insights and automated scoring directly against large unified datasets.
• Business users gain a single source of truth for analytics — backed by governance and security features that matter in regulated industries.

Voices From the Partnership

Executives from both organisations underscored the importance of this integration for the insurance sector.

Chris Halliday, Senior Director in WTW’s Insurance Consulting and Technology practice, said the integration “gives a more efficient experience for insurers.” He highlighted that Radar’s existing capability to deploy Databricks machine learning models — now embedded directly within workflows — means insurers can benefit from Databricks’ robust data and AI infrastructure.

From the Databricks side, Marcela Granados, Global Head of Insurance, said insurers can now bring all their data together into a “single, governed environment ready for Radar analysis.” By connecting Radar’s advanced pricing models to Databricks tools — including AI/BI Genie and Agent Bricks, powered by Unity Catalog — insurers can make faster decisions, enhance compliance, and innovate with greater confidence.

Strategic Implications for the Insurance Technology Landscape

The WTW–Databricks integration aligns with several important industry trends in insurtech:

1. Breaking Down Data Silos

Insurance analytics has historically been constrained by fragmented data. This integration helps unify data estates — bringing policy, claims, underwriting, and external datasets into a single governed environment. By doing so, insurers can leverage comprehensive, clean data for pricing and risk models.

2. AI and Machine Learning at Scale

Modern insurers seek to deploy machine learning models not just for experimental analysis but as part of routine risk management and pricing operations. Radar’s compatibility with Databricks AI infrastructure enables these models to operate on live data, reducing latency and accelerating insight cycles.

3. Enhanced Governance

Insurance is a highly regulated sector, and data governance — including auditability, lineage, and quality control — is paramount. Databricks Unity Catalog brings enterprise governance capabilities to Radar users, helping firms meet compliance obligations while maintaining analytical agility.

4. Automation and Workflow Efficiency

By automating what were previously manual steps, insurers can reduce operational bottlenecks and errors. Real-time or near-real-time data updates shorten analytics cycles, giving firms the ability to respond quicker to emerging market signals or risk exposures.

Competitive Positioning and Ecosystem Dynamics

WTW’s decision to integrate Radar with Databricks also positions the company strongly among analytics and insurtech providers. Many insurance software vendors offer modular analytics tools, but the ability to natively connect with a powerful data platform like Databricks — widely used across industries — gives WTW a competitive edge in terms of scalability and interoperability.

This move reflects a broader industry pattern where insurers and technology providers partner with enterprise data platforms to boost analytics performance rather than building proprietary systems from scratch. Such alliances can enable better use of advanced analytics, reduce duplication of technology investments, and facilitate integration with other enterprise systems such as business intelligence, dashboards, and reporting tools.

Broader Industry Context

The push toward unified data environments in insurance comes at a time when the industry faces multiple, simultaneous pressures:

• Inflation and rising claims costs requiring more accurate pricing and risk prediction.
• Increased regulatory scrutiny around pricing fairness, capital adequacy, and operational risk.
• Customer expectations for speed and transparency across underwriting, claims, and pricing decisions.

Tools that bring speed, governance, and advanced analytics to these core workflows are becoming essential. Radar’s integration with Databricks not only accelerates analytics but also fosters a richer ecosystem where insurers can leverage both proprietary and external data sources to stay competitive.

Conclusion: Building a Modern, Data-Driven Insurance Future

The launch of the Radar Connector for Databricks marks a meaningful step in how insurers manage and analyse data at scale. By eliminating manual data movement, improving governance, and enabling richer models through machine learning, WTW and Databricks are creating a more intelligent, unified ecosystem for insurance analytics.

In an industry where decisions hinge on data — from pricing to risk selection — the ability to harness that data dynamically and with robust governance is no longer a differentiator but a necessity. With this integration, insurers have a toolset that accelerates insight, supports compliance, and sets a foundation for continued innovation.

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