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    Moody’s Analytics Wins ESG Software of the Year

    June 2020

    Moody’s Analytics Wins ESG Software of the Year

    InsuranceERM Annual Awards 2020 - Americas - Winners

    Written by InsuranceERM.

    Moody's Analytics has developed cohesive scenario generation solutions to support its clients. These range from helping firms assess group-wide economic and regulatory capital, to developing capital management strategies, and pricing complex embedded guarantees and options.

    Moody's Analytics has focused on building robust, transparent, and quantitatively assessed strategic asset allocations and investment strategies that are well understood and scrutinised in the context of a company's liability profiles.

    As well as streamlining modelling processes by using the automation module to reduce production timelines and costs through automated execution and validation, the company has harnessed the power of cloud computing to support clients in accessing high-performance computing that aligns with their production requirements and budgets.

    Over the last year, the company introduced its Cloud Burst Service, which lets users run the Scenario Generator in the Moody's Analytics-hosted cloud environment. This provides access to thousands of computing cores on-demand, reducing runtimes from hours or days to minutes.

    At the same time, use of grid computing technologies delivers fast runtimes and the Application Programming Interface (API) allows users to run the Scenario Generator as part of a wider end-to-end automated process.

    Recent modelling enhancements include the introduction of the IFRS 17 Discount Curve services that deliver fully-fitted yield curves each quarter across a wide range of economies. This service is now updated with the company's latest research and views on the credit and economic impact of Covid-19, and a severe and critical pandemic scenario was released in March.

    The Moody's Analytics Scenario Generator also incorporates the development of a stress testing calibration framework to support the use of climate change scenarios and assumptions for real-world calibrations.

     

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