The leading web resource for financial technology
Sign in to bobsguide SIGN IN | REGISTER
bobsguide.com

Union Bank orders a second helping of SAS® for risk management

email this aricle - Union Bank orders a second helping of SAS® for risk management - CARY, NC - 9 February 2010 print this article - Union Bank orders a second helping of SAS® for risk management - CARY, NC - 9 February 2010
SAS® operational risk management software tops bank’s selection list on several fronts

Banks looking to garner advanced measurement approaches (AMA) for assessment and management of operational risk require a comprehensive framework for capital estimation, which incorporates loss events across the enterprise. With that advance need in mind, Union Bank, N.A., has selected SAS, the leader in business analytics software and services, to help manage risk more efficiently and with more rigor. Union Bank is familiar with the strength and quality offered by SAS risk management software as they selected SAS for credit risk management in May 2009.

Union Bank determined that SAS OpRisk VaR, a sophisticated, yet user-friendly analytic value at risk (VaR) model, would help the organizations slice, dice, drill down, adjust, trend and plot operational loss data at will, following a fully transparent, intuitive and sequential process.

“We saw SAS software rated highly by analyst research firms and customers for operational risk, so it was obvious they were more capable than others and would fit better within our organization,” said Greg Jones, Vice President of Operational Risk at Union Bank. “SAS offered a comprehensive solution that specifically addressed operational risk with customizable modeling capabilities. They were head and shoulders above the competition.”

In addition to the SAS reputation and external recognition, Union Bank was impressed with specific capabilities of SAS OpRisk VaR. The SAS software was the only product to offer “extreme value theory,” which is important for assessing risk for highly unusual events and “component sensitivity analysis,” which gauges how sensitive a model is to changes in certain parameters. In addition, the SAS solution was highly capable in its ability to weight internal and external loss data.

Comments (0)

No one has commented on this yet. Be the first!
Add your comment - Max 1000 characters used