Industry Data Models

Solvership’s Insurance Data Model is designed to simplify and optimize the data management needs of insurance companies.

With over 400 tables and support for multi-company, multi-currency environments, it provides a detailed framework for managing policies, claims, risk, and profitability. We’ve been developing our model since 2009, and today it enables insurers to consolidate data across systems and streamline regulatory reporting. It’s built to be flexible, allowing for continuous updates to meet the always-evolving regulatory standards and business needs.

One unique feature of our model is its focus on detailed actuarial and risk analytics: the Insurance Industry Data Model supports a comprehensive view of risk, enabling companies to assess their exposure more precisely, and manage their risk portfolios. This level of detailed insight into risk and actuarial processes is essential for making informed decisions and ensuring long-term business stability.

Talking about risks, our model comes with another beneficial feature — it can be implemented incrementally, ensuring that each phase delivers a fully functional solution. This approach reduces the risk of failure, allowing for seamless integration into existing systems without disrupting ongoing operations. Incremental delivery also means that updates and enhancements can be made more efficiently, as business needs evolve.

The model is highly customizable, designed to adapt to the specific requirements of different insurance sectors, such as health, life, or property insurance. This flexibility allows companies to fine-tune the model for their unique products and business processes, making it a versatile tool that can evolve alongside the business.

It’s also an ideal solution for operations in multiple regions or dealing with complex, cross-border operations — it simplifies reporting and decision-making across different markets and currencies, reducing the complexity of managing diverse portfolios.

• Managing detailed claims and policy analytics
• Supporting multi-currency and multi-company operations
• Automating regulatory reporting for compliance
• Tracking profitability and risk assessments
• Customizing data models for specific business needs