For all its technological complexity, artificial intelligence (AI) rests on one very simple foundation: data.
And it’s here that Databricks has put a stake in the ground, claiming 50% of the Fortune 500 as customers since its founding in 2013. As global head of financial services Junta Nakai told PYMNTS, educating those clients — and prospects — is top priority.
“Especially in financial services, they want to use the most important asset that they have today more effectively, and that asset is data,” Nakai said. “And then to do so, you need to go up this maturity curve. The maturity curve breaks down to something simple, which is you must modernize your tech stack. You need to democratize access to data right throughout your company, and then you must transform your company. That’s what we do with our technology. And simply put, it stores all your data in a single place, and do all the things that you do with your data come from that.”
Sounds simple. But Databricks takes its mission seriously. In fact, right on its homepage is a tutorial, “Migrating From A Data Warehouse to A Data Lakehouse For Dummies.” One of its taglines summarizes its go-to-market approach: “Databricks brings AI to your data to help you bring AI to the world.” It does that by giving enterprises the ability to create their own generative AI models, which can be deployed and monitored at scale.
Read more: Why Every Business Now Wants a Data Lakehouse
A good example of how it works can be seen in Databricks’ work with Block. The parent company of Square and Cash App uses machine learning to detect and defend against fraud and enhances the user experience with personalized recommendations, which requires a deep understanding of customer needs and preferences.
It’s also important in the company’s drive to increase financial inclusion. Block works with Databricks to consolidate and streamline its data, AI and analytics workloads. According to Block executives, the move positions it for what it calls “the forthcoming automation-driven innovation shift” in financial services.
That shift, and the ability to enhance the consumer financial services experience using AI, is critical for the Databricks value proposition. Nakai says it will lead to the ability to hyper personalize offers and messaging. It also creates the ability to inform that personalization by using AI to scour unstructured data and text to understand the customer at a different level.
The potential ramifications of getting this information wrong can be substantial. Nakai said he recently became aware of an automotive dealership, for example, that set out to integrate AI into its marketing without this due diligence. It ended up creating ads that sent consumers to a rival dealership.
Nakai’s background is in securities sales and trading, which he did for 14 years at Goldman Sachs. He’s familiar with the frustrations of manual work, slow trading programs and even slower Excel files. He realized early on that the future of his business was going to be at least partially dictated by algorithms, and now he sees that future in action.
“I think one of the reasons we’ve been so successful is because AI is a CEO-level priority at every single company in the world,” Nakai said.
“AI is going to be critically important, and we think cloud is the future. All the things that you need to futureproof your architecture is there, but it also is sort of your eye on the prize for AI in the future. What we provide is the opportunity to modernize your legacy system so you could set yourself up for those kinds of things in the future.”
Of course, legacy systems and financial services still belong in the same sentence. Nakai believes advanced AI has not yet been deployed at most financial institutions because of that legacy infrastructure and the inherent risk-averse nature of the business.
But that’s changing. He sees major banks flowing more of their innovation budgets toward AI and that executives know that if they want to compete with the FinTechs nipping at their heels that AI will be an important competitive factor.
“The secret sauce that the winning banks are going to embrace is capitalizing on their capital, scale data and people,” he said. “You need to do that extremely well.”
“That’s how the future of banking is going to be created. Because the future of finance will be three things. It’s going to be instant. It’s going to be inclusive. And I think it’s going to be invisible, meaning like using Uber. You don’t even think about paying because it’s part of the experience.”
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