Any financial services firm using AI must revisit its approach to model risk management. The reason is that AI models are evolving faster than the rules-based models that were standard previously. If AI models perform inadequately, major operational losses can grow quickly. Watson OpenScale helps
With the amount of choices surrounding big data analytics, data lakes and AI, it can sometimes be difficult to tell fact from fiction. With more than 40% of organizations expecting AI to be a “game changer,” it’s important to have a complete picture of the capabilities and opportunities available.
With its electro-light tulip garden, disco ball-adorned trees and no stone-left-unturned music lineup, "Denmark’s Most Beautiful Festival" aims to surpass guests’ expectations on safety, comfort and entertainment, from its uncannily clean bathrooms down to its whimsical camp-in-a-beer-can glamping
James Fisher & Sons had hearty ambitions to build predictive maintenance capabilities for its customers' subsea cables -- but lacked the right data to do so. In a creative pivot, the IBM Data Science and AI Elite team delivered more than what the heritage engineering company bartered for --
The future of banking is transforming. From changing customer behavior and expectations, rapid innovation in digital technology, burgeoning regulatory requirements, and the macroeconomic environment, the very definition of financial services is changing. For banks to stay relevant, they need to
Making the case for AI, or any nascent technology for that matter, can be a struggle for companies today. While large enterprises know they need to be fast, agile and innovation-obsessed to survive disruption, their age-old policies, antiquated systems, disconnected data and entrenched corporate
Among organizations investing in AI hardware, software or services, more will buy IBM and rely on Watson than any other vendor. This according to a new IDC report which names IBM as 2018’s market leader in AI. So just what sets apart IBM as leader of the AI provider pack?
Seizing the AI opportunity to tap new sources of energy inspired one ExxonMobil leader to take a collaborative approach to its big data problem. Now she’s been recognized by IBM as a top woman AI leader.
The best data catalogs can automate the process to collect, classify and profile data to ensure the highest standards of quality. Here are three popular use cases detailing why companies are moving towards IBM’s Watson Knowledge Catalog.
It’s no surprise: most companies working with stream data today say they are planning to make changes to drive greater value. Advancements in machine learning (ML) and very-high-speed data persistence for real-time analytics are reshaping strategies and architectures. In addition, 88 percent of
In business, aspiring to world-class is not enough when your competitors are already there. About half of the companies listed on the S&P 500 will be replaced over the next 10 years. Compared to the past, what’s unique about the disruption happening today is the rapid pace of change. During
Capitalogix is a hedge fund, but it’s really a data science firm in disguise. They work to understand and exploit capital markets by building custom data science models that can analyze massive amounts of data from as many sources as possible. Capitalogix’s need for high-performance analytics and
Many companies struggle with outdated, duplicate or incorrect customer data. At Localiza, we can go beyond identifying the customer by name, profession and role -- to customizing the entire experience based on the customer’s past history with us. With this 360-degree view of each customer’s current