FICO, an analytics software company based in Bozeman, Montana, USA, operates in over 80 countries. The company's focus is to assist businesses in making better decisions that contribute to growth, profitability, and customer satisfaction, using Big Data and mathematical algorithms to predict consumer behavior. FICO offers software and tools that are widely used in various industries for risk management, fraud detection, customer relationship enhancement, operational optimization, and compliance with stringent governmental regulations. Its flagship product, the FICO Score, is a standard measure of consumer credit risk in America. Embracing open-source standards and cloud computing, FICO's solutions aim for flexibility, swift deployment, and cost reduction. Founded in 1956, FICO is an innovator of analytical solutions like credit scoring and other pivotal decision-management technologies such as predictive analytics, business rules management, and optimization.
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I like how easy the syntax of the Mosel programming language which is used to code in FICO Xpress Optimizer is. We had no difficulty translating the mathematical constraint inequalities we formulated for our Mixed Integer Programming (MIP) problem into the Mosel programming language.
What I enjoyed most of the product is te interactivity between programation language and how useful is to teach Linear Optimization
The speed of the package (in solving optimization models) and its fantastic support
At first, it was difficult for us to understand when the solver gave the output as an 'infeasible' solution i.e. just a bunch of zeroes as it is never explicitly mentioned in FICO Xpress Optimizer.
What I disliked more was the few helpful tools to use it well. But tool is so good that it may not be necessary.
Some component libraries like BCL are a bit old and slower. We just don't use those, and keep working with the main XPRS libraries