FICO Xpress Insight Empowers 8+ Million Python Developers to Foster Collaboration Between Data Scientists and Business Users, Drastically Accelerating Project Deployment

Rhea-AI Summary

FICO has enhanced its FICO® Xpress Insight platform by adding native Python support, allowing Python's 8.2 million users to develop sophisticated analytic models effectively. This upgrade enables business professionals to easily build applications that operationalize advanced analytics, bridging the gap between data scientists and business users. The integration aims to improve project deployment times significantly and enhance decision-making processes across industries. The platform emphasizes interoperability, helping enterprises leverage data insights to better serve customer needs.

Positive

• Introduction of native Python support to FICO® Xpress Insight enabling 8.2 million Python developers to create advanced analytic applications.
• Improves project deployment speed, significantly reducing time from development to operationalization.
• Enhances collaboration between data scientists and business users, translating complex models into user-friendly applications.

Negative

• None.

SAN JOSE, Calif., March 1, 2021 /PRNewswire/ --

Highlights:

• The addition of native Python support to FICO® Xpress Insight enables Python's 8.2 million users to empower business professionals with easy-to-use applications that can execute sophisticated analytic models.
• With FICO® Xpress Insight business users and analysts can work with any advanced analytic model in business terms to perform simulations, compare scenarios and visualize outcomes to make better informed decisions.
• Python developers can now build and operationalize Python based models all within a single framework, reducing time to deployment by orders of magnitude.

FICO, a global analytics leader, today announced it has added native Python support to FICO® Xpress Insight. Xpress Insight enables data scientists to quickly build and deploy any advanced analytic or optimization model as a powerful business application. 

Across industries, data scientists create powerful models to solve complex business problems. Yet, according to most industry analysts, more than half of data science projects are never fully deployed. FICO Xpress Insight helps translate between the data scientist and the line of business user by taking highly complex analytic or optimization models and turning them into simple point and click applications that help them make real business decisions.

"It's a huge waste of time and resources when the models don't reach the intended business users," said Bill Waid, vice president and general manager of FICO® Decision Management Suite. "The real value of highly complex analytic models comes when they're in the hands of the business users and become an integral part of their decision making process."

The newest update to Xpress Insight enables the 8.2 million developers that use the popular coding language Python to rapidly build business applications that can execute sophisticated analytic models. Getting analytic applications into the hands of business users allows business leaders to make more informed decisions, perform simulations, compare scenarios and visualize outcomes.

"Python is one of the most productive tools for our digital and data science initiatives. Having Python supported in Xpress Insight helps us smoothly build end-to-end applications from data preparation, to modeling, to visualization," said Sitao Zhang, data scientist, Supply Chain Digital and Data Science, Johnson and Johnson. "This new feature has not only made our applications more coherent during programming and development, but it also helps us deliver a more user-friendly experience to the business professionals using the applications to drive results."

FICO® Xpress Insight is part of the FICO® Platform, a decisioning foundation critical for enterprises' digital transformation. The platform is designed to eliminate data siloes and enable interoperability between enterprise applications. By connecting data-derived insights from disparate business units, enterprises can respond quickly to customers' immediate needs and anticipate their future demands, resulting in deeper, more engaging customer experiences.

About FICO
FICO (NYSE: FICO) powers decisions that help people and businesses around the world prosper. Founded in 1956 and based in Silicon Valley, the company is a pioneer in the use of predictive analytics and data science to improve operational decisions. FICO holds more than 195 US and foreign patents on technologies that increase profitability, customer satisfaction and growth for businesses in financial services, telecommunications, health care, retail and many other industries. Using FICO solutions, businesses in more than 120 countries do everything from protecting 2.6 billion payment cards from fraud, to helping people get credit, to ensuring that millions of airplanes and rental cars are in the right place at the right time.

Learn more at https://www.fico.com

Join the conversation at https://twitter.com/fico & https://www.fico.com/en/blogs/

FICO is a registered trademark of Fair Isaac Corporation in the US and other countries.

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SOURCE FICO

FAQ

What is the significance of Python support in FICO® Xpress Insight?

The addition of Python support allows 8.2 million developers to create and operationalize advanced analytic models more efficiently, bridging the gap between data scientists and business users.

How does FICO® Xpress Insight improve project deployment?

The platform significantly accelerates project deployment times, enabling faster integration of analytic applications into business processes.

What industries can benefit from FICO® Xpress Insight's new features?

Various industries utilizing data science can benefit, as the platform allows for better decision-making and enhanced collaboration on analytic models.

What are the key features of FICO's enhanced analytics platform?

Key features include the ability to build user-friendly applications from advanced analytic models and improve interoperability between enterprise applications.