Monetizing the Data Ecosystem\n\nBy Anand Pandya\nMay 23, 2025 in Data, Emerging Payments, Featured Content\n\nForget whatever AI buzzword is trending this week. Focus instead on what truly turns data into dollars. For IT leaders in financial services, today’s opportunity isn’t about traditional analytics, automation, agentic workflows, LLMs, or generative AI. It’s about monetization—specifically, unlocking the monetization potential inherent within the data ecosystem itself.\n\nTo back up a bit, we’ve all heard the modern truism that data is the new gold. Of course, that truism comes with the caveat that if you don’t know how to extract real, scalable value from data, then it may as well be mud.\n\nSo conceptually, all the trending IT “musts”—cloud migration, automation, agentic AI, and the other assorted buzzwords of the day—don’t mean squat unless you actually start extracting value from them. And that data-driven value is not found in faster queries, a pleasant chatbot, or better analytics and insights. We’ve paralyzed ourselves with analytics and insights. I’ve never met anyone who uses their bank’s voice activated digital assistant. And believe me, nobody wants another dashboard.\n\nThe actual value shift is monetization—companies generating revenue not just from their core services and products, but also from applications and capabilities driven by the data they are generating within an ecosystem that enables useful new stuff worth paying for.\n\nWhat does that look like in real life?\n\nFrom Cost Center to Revenue Engine\n\nMonetizing data requires shifting the perceived purpose of financial services IT. Traditional platforms—whether on-prem, cloud, or hybrid—have always been viewed as high-cost centers: big infrastructure CapEx, complex operations, crippled by regulations, slow to innovate. Any of this sound familiar?\n\nBut moving from legacy platforms into modern cloud ecosystems places you within thriving data-sharing marketplaces. Rearchitecting your organization’s IT operations and data stack—not as a simple lift-and-shift, but through migration and refactoring within of AWS, Snowflake, Azure or whichever modern data ecosystem you choose—directly impacts functionally and business models. It also enables IT to evolve from a cost center into a potential profit center.\n\nWithin such ecosystems, you can accelerate time to market and reduce infrastructure overhead with a fully managed and elastic scaled platform. That’s been the cloud sales pitch all along. But more importantly, you can now enable data monetization. This may take the form of simply supplying data-as-a-service to others in the marketplace for a fee. Or this can involve using your data to craft an experience-as-a-service. The ecosystem supplies a ready mechanism for new forms of data services, which create new streams for revenue generation.\n\nThe model supports a kind of bi-directional flow. Typically, there’s either a complete embedding of an application directly inside of the ecosystem that enables the customers to access the service within their own environment on AWS/Snowflake/Azure/etc.—effectively not just sharing your data, but sharing that entire experience seamlessly within a harmonized ecosystem. From a financial services perspective, this could be risk analytics, fraud detection, compliance automation, and other components packaged as an embedded application. Thus, a bank doesn’t have to send their data to risk metrics anymore, they can just get all of those calculations as-a-service directly on their data in their own house securely.\n\nThe other direction functions more like a power button, where an organization migrates their data backbone to run on Snowflake or GCP or whatever as a back end, but they maintain their own application interface as a kind of “managed motif.” The organization’s platform operations get the benefits of the data backbone and the sharing mechanisms of the data ecosystem, but the application is their own interface, and the new capabilities are packaged and supplied “behind-the-scenes” to that organization’s customers through their familiar interface. Within such data ecosystems, entirely new lines of business become possible.\n\nRedefining Business\n\nThrough this lens, IT strategy is no longer a technical exercise. You have to overlay modernization investment with monetization opportunity and understand how that could change your commercial model, churn rates, and actual net new products and services being offered. And you have to decide how to align those new monetization and commercial strategies within the perpetually expanding portfolios of your data ecosystem and the fast-evolving needs of both current and prospective partners and customers.\n\nThis is a dynamic new arena where data monetization opportunities can redefine the nature of the FSI industry and an organization’s role in it. Late last year, one company with a decades-long lineage in post-trade processing and tax reporting software began piloting a platform that essentially offers transformation-as-a-service. They packaged their own data-agnostic integration technology and real-time data access and intelligent automation and started offering it to select wealth management customers in their data ecosystem to, in turn, simplify their own operations and more easily start innovating their own new services and experiences. The implied as-a-service network effects from these types of new products will only proliferate across data ecosystems.\n\nThe cloud is the future, automation boosts efficiency, and well-executed AI is a game changer. But the incessant hype around them belies a simple truth: these are just tools of the trade. None should distract from the true opportunity in financial services and modern business alike—data is an asset to be monetized.

Monetizing the Data Ecosystem

The article discusses how financial services organizations are shifting from traditional IT infrastructure to modern cloud ecosystems to monetize data. It emphasizes the transition from cost centers to revenue engines through data-as-a-service and experience-as-a-service models, leveraging platforms like AWS, Snowflake, Azure, and GCP to enable new revenue streams and redefine business strategies.