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Using big data to solve the xva compute challenge - Risk.net interview

Derivatives pricing has changed dramatically over the past decade with an explosion in the number of valuation adjustments (XVAs) required. Traditional credit valuation adjustment systems are struggling to accurately calculate and manage these multiple XVAs and deliver a consistent view of all the trades in a portfolio.

In this video, Stuart Nield and Abhay Pradhan of IHS Markit’s Financial Risk Analytics team discuss:

  • The key challenges of derivatives valuation (MVA, CVA, KVA)
  • Solving the compute and data challenge
  • Replacing legacy systems using open source technology
  • New technology cost savings and efficiency gains
  • Preparing for a tech-driven future

Learn more about XVA and Counterparty Credit Risk

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