France's leading provider of life insurance, CNP Assurances has adopted Numerix’s Economic Scenario Generator as a fast and accurate solution for its derivatives and liabilities pricing. Built on the world’s most comprehensive capital market model library, Numerix CrossAsset, Numerix ESG is a sophisticated stochastic simulation framework for producing risk neutral and real world economic scenarios within a consistent modelling environment.

CNP Assurances required more accurate projections of both risk neutral and real world scenarios to assess, and better understandstatic and dynamic modeling assumptions for fund allocation strategies and more generally for ALM studies.

Consistent Modelling Framework for Risk Neutral and Real World Scenarios

Numerix ESG model dynamics are consistent for both risk neutral and real world scenarios. The unique hybrid model framework of Numerix ESG enables the customization of all model and calibration settings for scenarios giving users full control of scenario generation. With Numerix, CNP Assurances is able to select desired models based on underlyings, and use them as building blocks to create unified hybrid models that capture correlations among asset classes.

“The flexibility of Numerix models and transparency that comes with the ability to view and customize all model and calibration settings was central to our interest for Numerix ESG,” said Jean-Philippe Medecin, Head of ALM, Investment Division at CNP Assurances. “With a unified modelling framework for risk neutral and real world scenarios, we’re able to power applications with robust, consistent scenarios for our ALM model. We’re also confident in our utilization of Numerix ESG generated real world scenarios for benchmarking purposes. This also helps us with our ALM studies.”

“Numerix ESG brings together risk neutral modeling dynamics for pricing and hedging, with stochastic real world scenarios for projecting forward liabilities for capital and reserving requirements,” said Steven R. O’Hanlon, Chief Executive Officer & President of Numerix. “With a consistent modelling dynamic between risk neutral models and real world models, users can build out a nested stochastic framework that’s not only consistent and defensible, but optimized for computational run time.”