RiskSpan Releases Summer 2018 Edge Platform Update

ARLINGTON, Va.Aug. 9, 2018 — RiskSpan announced today that it has released the Summer 2018 production update to its commercially-available RS Edge Platform. RS Edge is a SaaS platform that integrates normalized data, predictive models and complex scenario analytics for customers in the capital markets, commercial banking, and insurance industries. The Edge Platform solves the hardest data management and analytical problem – affordable off-the-shelf integration of clean data and reliable models.

Major enhancements have been included in the Agency MBS Analytics module, the Portfolio Whole Loan Analytics module, and the Portfolio Market Risk Analytics module.

Across the platform, RiskSpan is making 12 GSE/Agency and other third-party proprietary datasets available for historical and predictive analytics. New datasets include both Fannie Mae and Freddie Mac CRT (credit-risk transfer) data that is especially interesting to the mortgage investor and insurance communities.

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RiskSpan has also made available the Edge API that makes it easier than ever to access large datasets for analytics, model development and benchmarking. Major quant teams that prefer APIs now have access to normalized and validated data to run scenario analytics, stress testing or shock analysis. RiskSpan also makes data available through its proprietary instance of RStudio and Python.

“RiskSpan’s Edge Platform is a cloud-native SaaS offering that eliminates the costly hurdles involved with onboarding new data sets typically seen in legacy on-premise solutions. Our customers are excited about having quick access to model-ready data and analytics, and our data and modeling partners are excited about having us as a reliable distribution channel in the marketplace,” said CEO Bernadette Kogler.

Suhrud Dagli, CTO explained, “With our platform, users don’t have to struggle with procuring and configuring additional or new secure infrastructure. Our team works to on-board, normalize, analyze and model new data sets for them, which not only cuts costs significantly, but also delivers better analytics to the business.”

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