SAS® Underwriting Risk Management for P&C Insurance

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Reduced volatility.
Greater competitive advantage.

Blend actuarial and financial techniques to accurately value P&C insurance liabilities on both an accident- and underwriting-year basis. Only SAS delivers a single, flexible high-performance analytics environment for performing loss estimation, reserving and risk management analysis.

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Accurately model losses and estimate reserves. 

Calculate loss reserves across all product lines and segments using prebuilt market-standard methodologies – link ratio, chain-ladder, Mack, Cape Cod, Bornhuetter-Ferguson, etc. You can run multiple models and compare results, and even combine methodologies to get better estimates. You can also add expert judgment to model results to strengthen outcomes.  

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Comply with regulations – Solvency II and beyond.

Analyze all material P&C underwriting risks, and perform risk-based capital calculations to comply with Solvency II and other P&C regulations. Our solution supports the standard model approach to calculating the solvency capital requirement (SCR). And flexible reporting capabilities enable you to create additional regulatory and management reports to fit your business needs.

Underwriting Risk Management for P&C Insurance screenshot on monitor showing alternative scenario testing.

Reduce volatility.

Fully understand how different economic factors will affect your balance sheet. Then use that knowledge to strengthen and enhance your risk decision strategies. By stress testing your liabilities against sudden and dramatic changes in market conditions, you can ensure solvency – and success – over the long haul.  

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  • Fully integrated, end-to-end environment. Delivers a full spectrum of powerful features – from data management, to advanced risk analytics, to reporting – in a single, comprehensive solution.
  • Flexible risk analysis framework. Provides a single management platform and modular structure that meets the needs of multiple business divisions, and evolves to meet changing risk analysis needs.
  • Insurance-specific data model. Serves as a single source of information for your enterprise risk data warehouse.
  • Integrated data management. Improves data quality by reducing data inconsistencies, and includes prebuilt capabilities for loading data from the data model to your risk solutions.
  • Faster performance. Delivers faster analytical results via a massively parallel processing, in-memory execution environment.   
  • Scalable architecture. Scales smoothly from a single-server to grid computing environment, for efficient use of hardware resources and reduced IT costs.
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