Two European insurers, ARAG (Düsseldorf) and La France Mutualiste (Paris), have selected SAS Risk Management for Insurance to consolidate risk management capabilities and address regulatory compliance needs associated with Solvency II.
ARAG, which provides personal and commercial legal insurance, sought a comprehensive risk platform for data management – from risk calculations to reporting – to leverage compliance for business needs. The insurer selected SAS Risk Management to establish a common technology platform for all divisions, worldwide subsidiaries and insurance classes, according to a SAS statement. The solution will give ARAG its first-ever financial overview of the risks within the group, and deliver valuable new information and tools for corporate management while enabling Solvency II compliance, the SAS statement asserts.
“The key for us is the end-to-end approach,” comments Wolfgang Mathmann, head of Group Risk Management, ARAG. “The platform must model and calculate risks while managing risk data centrally for the entire group. It must also provide information through regulatory-compliant reports.”
La France Mutualiste required a consolidated risk platform comprising data collection, reporting and risk analysis in order to meet Solvency II requirements, according to a SAS statement. The mutual savings and retirement products company based its selection on both the solution’s technology merits and the vendor’s industry expertise, according to SAS.
The vendor describes SAS Risk Management for Insurance as a comprehensive solution for performing risk analysis and risk-based capital calculation for insurers. The software enables organizations to take a proactive approach to risk management, and at the same time align the process with business strategy, according to the vendor. SAS helps life and P&C insurance companies to adopt a Solvency II standard model approach for calculating risk-based capita. The solution is built on what the vendor characterizes as a robust data management and reporting platform that includes an insurance-specific data model for complex risk analytics.