Fair Isaac Corporation (FICO) recently launched the latest version of the FICO Xpress Optimization Suite to solve complex real-world problems of exceptional size and complexity at an enhanced speed to assist in delivering prompt business decisions. This latest version of the software is the only optimization software available in the market which proposes to address multiple complex optimization problems.
The updated model addresses the challenges faced by organizations related to Big Data and helps them to develop and deploy optimization applications to reach an optimum solution. The optimization software is equipped with 64-bit ultra-large-scale optimization, which helps in solving gigantic problems.
Additionally, this version has an add-on feature - Xpress- NonLinear, which simulates reality and establishes the true nonlinear relationships between decisions and outcomes. Unlike traditional linearization approaches, which use a sample of data from the solution space, the nonlinear model can use millions of variables and constraints to arrive at an optimum solution.
Fair Isaac’s Xpress Optimization Suite is likely to help its diversified clienteles like global banks, retailers, utilities and professional sports leagues to address complex problems that were otherwise unsolvable. These solutions are expected to equip them to take informed decisions for the most efficient and profitable use of capital, human resources, and technology assets.
Fair Isaac is a leading predictive analytics and decision management software company. The company’s analytics software has helped multiple industries to administer risks, avoid frauds, make profitable decisions and maintain strong customer relationship.
Fair Isaac currently carries a Zacks Rank #4 (Sell). Relatively better players within the Computer and Technology sector worth mentioning include AVG Technologies N.V. (AVG), Alliance Fiber Optic Products Inc. (AFOP) and Akamai Technologies, Inc. (AKAM), each holding a Zacks Rank #1 (Strong Buy).Read the Full Research Report on AKAM
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