LSEG Launches Open Risk Analytics on MaaS

LSEG says its Open Risk Analytics service, an offering within its post-trade solutions business, has been added to its Models-as-a-Service (MaaS) marketplace, as part of an effort to expand client access to quantitative risk models.

Delivered through LSEG’s Analytics API, the hosted service enables firms to access risk analytics through various development tools, including Visual Studio Code and JupyterLab, AI-enabled workflows via open standards like Model Context Protocol (MCP), and LSEG AI partners, including Microsoft Copilot. Current models available cover major asset classes including interest rates, inflation, FX, equity and commodities. They also support multiple calculations such as P&L Explain, stress testing, sensitivity analysis, cashflow and stressed cashflows, Historical VaR, Potential Future Exposure and Credit Valuation Adjustment.

“By enabling portfolio-level calculations and embedding them into AI-driven workflows, we are helping clients rethink traditional risk processes, unlock greater automation, efficiency, and insight,” says Aysegul Erdem, head of modelling solutions at LSEG. “Combined with LSEG’s analytics ecosystem, this creates powerful synergies for managing risk across enterprises.”

Stuart Smith, director, Post Trade Solutions, LSEG, adds, “Risk analytics only create value when firms can operationalise them. Hosted delivery, curated market data and transparent models give clients a practical way to run portfolio-level risk calculations such as Value at Risk, understand their risks with stress scenarios and run exposure analytics at scale.”