Press Releases

Major Upgrade to
Leading Risk Analysis Software


15 January 2008, Ithaca, NY - Palisade Corporation, the leading developer of analytic software for decision support, is pleased to announce the release of a comprehensively upgraded new version of @RISK. An add-in to Microsoft Excel, @RISK performs Monte Carlo simulation to identify and reduce uncertainty in any decision, course of action, or process. One of the first quantitative tools for business intelligence, @RISK was introduced in 1987 and has held a substantial sales lead in the field of risk analysis since then. It is available in six languages and used by more than 150,000 people in sectors that range from finance and insurance to engineering and construction, from defense to energy to pharmaceuticals. Under development for the past three years, @RISK 5.0 has been redesigned from the ground up to facilitate corporate-wide collaboration and model sharing. Version 5.0 provides total and seamless integration with Excel via its completely new Office 2007-style interface.

Customer-Driven Functionality Unavailable Elsewhere
Many of the improvements and additions to the new version are customer-driven. They are Palisade’s responses to needs and ideas expressed by decision-makers who use the tools on a day-to-day basis—and they are not commercially available elsewhere.

Here are some highlights unique to @RISK 5.0:

  • All-New Interface allows users to analyze risk without ever leaving their Excel spreadsheet
  • @RISK Library, an SQL database that allows sharing of specific probability distributions and simulation results
  • Compound Function eliminates thousands of separate frequency and severity distributions by combining them into a single function

Additional improvements in @RISK 5.0 include:

Optimization in the Industrial Edition
The Industrial edition of @RISK 5.0 includes the all-new RISKOptimizer 5.0, the powerful optimization add-in to Excel. RISKOptimizer combines genetic algorithm optimization with Monte Carlo simulation to solve complex optimization problems—like resource allocation, for example—under uncertainty.

For more information, contact:

Randy Heffernan
Tel: +1 607-277-8000
Fax: +1 607-277-8001

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