This article is part of a VB Lab Insights series paid for by Capital One.
Most people are familiar with major technology platforms like iOS, Windows and AWS. Platforms, in their essence, are a group of technologies that serve as a base from which to build, contribute, experiment and scale other applications. They enable much of today’s most advanced technology capabilities and cutting-edge customer experiences.
In order to keep pace with the scale and complexity of the technology capabilities brought by big data, AI and machine learning (ML), many companies are developing sophisticated internal platforms of their own. In fact, Gartner predicts that by 2025, cloud-native platforms will serve as the foundation for more than 95% of new digital initiatives — up from less than 40% in 2021.
In my experience, enterprise technology platforms have been transformational: they enable cross-functional teams to test, launch and learn at a rapid pace; reduce duplication and standardize capabilities; and provide consistent and integrated experiences. In short, they help turn technology into a competitive advantage.
Increasingly, organizations are becoming more adept at delivering top-notch customer experiences by leveraging cloud-native platforms like Kubernetes that can run large AI and ML workloads. Capital One’s move to become the first U.S. financial institution to go all in on the cloud and our ability to re-architect our data environment have been integral to expanding our cloud-based platform capabilities. With that strong foundation, we’re better able to leverage big data to build new ML capabilities on top of our enterprise platforms to accelerate, enhance and deliver on new, more meaningful customer experiences.
Much of our work in this area is already showing impactful results for the business and for our customers. For example, our fraud decisioning platform was built from the ground up to make complex real-time decisions. By leveraging massive amounts of data and enabling model updates in days (as opposed to months), the platform helps protect millions of customers from card fraud and can be used by various stakeholders across the enterprise.
Based on my experience leading teams to deliver enterprise technology platforms, there are important lessons and best practices I’ve learned along the way:
When a team has a strong culture backed by the right platform technology, the possibilities are endless. By combining cloud-native platforms with data at scale, companies can better advance and experiment with newer, more innovative products and experiences. And when those experiences enable end users and customers to achieve exactly what they need, when they need it — that’s revolutionary.
Marcie Apelt is MVP, ML/AI Product at Capital One.
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