Step 2 to a successful Solvency II approach: Calculation and analysis of indicators

This article is the second in a five-part series drawn from our expert ebook “5 steps to a successful Solvency II approach”. Having established solid data foundations in Step 1, we now move into the heart of the actuarial engine: how to produce, industrialize, and interpret the key indicators that drive your Solvency II framework.

Under Solvency II, this step is at the heart of the prudential framework: it transforms data into economic indicators, and then into actionable insights for analysis and decision-making.

These calculations are based on forward-looking cash flow modeling, incorporating economic, behavioral, and technical assumptions. They must be robust, reproducible, and capable of accurately reflecting the specificities of portfolios and products.

Beyond their production, their relevance depends on their ability to capture product complexity (options, guarantees, policyholder behavior), evolving market conditions, and the sensitivity of results to key assumptions.

In this context, insurers must rely on high-performance and flexible calculation engines capable of handling advanced actuarial models and adapting to various use cases (life, non-life, health).

Enhanced actuarial libraries, combined with strong configuration and customization capabilities, make it possible to balance the standardization of calculations with business-specific requirements. This combination is essential to ensure both reliability and agility in response to regulatory changes and new products.

In this perspective, some market solutions include preconfigured cash flow generators, while allowing model customization or integration of external cash flows, ensuring comprehensive actuarial coverage while reliable and actionable results.

Today, insurers must be able to reduce calculation times, run multiple scenarios and iterations, and deliver results within timeframes that align with closing cycles.

The standardization of calculation processes has become essential to ensure responsiveness, reliability, and analytical capability. It also frees up time for actuarial and risk teams, allowing them to focus more on interpreting results than on producing them.

This analysis includes identifying key drivers of variation (financial markets, assumptions, portfolio changes, methodological changes), decomposing SCR by risk modules, analyzing diversification effects, and assessing sensitivity to key parameters.

Throughout the closing process, actuarial, risk, and finance departments must have access to dynamic dashboards that allow them to monitor key indicators in order to understand, manage, communicate, and justify their evolution.

Today, regulatory expectations go beyond calculation accuracy, they also require explainability. Any significant variation must be understood, documented, and quickly communicated to stakeholders: senior management, auditors, and supervisor.

In this context, integrating result explainability tools becomes a powerful lever. It enables insurers to quickly identify explanatory factors, enhance analysis reliability, and reduce the risk of misinterpretation. Explainability becomes a key driver of operational risk control.

They support ORSA exercises, stress tests, and multi-year projections by providing a forward-looking view of risk profile and solvency ratio. These analyses inform strategic decisions, particularly regarding asset allocation, underwriting policy, risk management, and distribution strategies.

The ability to project solvency under various economic scenarios becomes a key factor in anticipating risks and securing financial trajectories.

This alignment involves harmonizing cash flows, ensuring consistency of assumptions, and converging modeling approaches.

A unified management of data and models helps limit discrepancies between prudential and financial views, reduce operational costs, and enhance the reliability of analyses.

Actuarial calculations, enhanced by advanced analytical capabilities and explainability tools, become a powerful lever to understand the risk profile, anticipating changes, and guide decision-making.

In this context, relying on integrated solutions that combine computational power, model flexibility, and analytical depth is a key asset for transforming a regulatory requirement into performance and strategic management tools.

Want to go further? Download our full ebook “5 steps to a successful Solvency II approach” and get the complete picture.