Sophis, a provider of cross-asset, front-to-back portfolio and risk management solutions, announced a significant partnership with Platform Computing, the cluster, grid and cloud management software for the financial services industry. Sophis is now offering an integrated solution with Platform Symphony for users in the banking, insurance and investment management sectors to distribute resource-hungry calculations such as P&L and sensitivities calculations, instrument pricing, risk simulations and value at risk (VaR).
Sophis and Platform carried out a benchmark test on their joint solution at IBM's Product and Solution Support Centre (PSSC) in Montpellier, France during July 2010 on IBM's latest powerful hardware: IBM Power 750, IBM XIV Storage System, IBM System x3850 M2 and IBM BladeCenter HS22.
Using OTC structured products, the test ran a historical VaR calculation on a multi-asset portfolio with 32,000 positions, which was representative of a true portfolio. The test, computing VaR calculations with 270 historical scenarios, took four hours using less than 300 nodes and less than 90 minutes using slightly over 800 nodes with no apparent limitation and linear scalability.
Samer Ballouk, Head of Product Management and Business Development at Sophis, said: "The results of this benchmark with Platform Computing are very good news for our customers, who have increasingly demanding risk management and portfolio valuation requirements. By speeding up calculations using a grid approach, they can introduce an intra-day VaR calculation, for example, and comply with the latest guidance on risk management and reporting."
Tripp Purvis, Vice President, Business Development at Platform Computing said: "Calculating risk is one of the most critical processes at any financial institution. Our partnership with Sophis will allow financial services companies that use our integrated solution to run simulations and complete analyses in a timely manner. In addition, the benchmark results show that users will benefit from the ability to distribute workloads across a grid infrastructure for maximum resource use."