This is part two of a three-part series on data aggregation sponsored by MX. MX enables financial institutions and fintech providers to grow faster, reduce costs, and deliver exceptional customer experience. Founded in 2010, MX is one of the fastest-growing fintech providers, partnering with more than 1,800 financial institutions and 43 of the top 50 digital banking providers. Learn more about MX here. As we’ve been reporting on lending, banking, personal finance, and investment technologies, we noticed that data aggregation was an increasingly important component for a lot of fintech -- sometimes even critically important for products themselves. The seminal moment for data aggregation in the U.S. occurred in December 2018, when upstart Plaid closed a $250 million investment on a multibillion dollar valuation. Soon after, Plaid quickly acquired Quovo, another top competitor. And while Europe has passed regulation requiring banks to share data with the apps and software their account holders request, the U.S. isn’t quite there yet. “The largest tension which exists in this space is the question around whether money should be regulated,” said Brandon Dewitt, co-founder and CTO at MX. For example, take a look at a popular app like Mint, which was bought by Intuit in 2009. 10 million users turn to the app to create budgets, pay bills, and manage their money. To do that effectively, a user connects all his bank and credit card accounts. Behind the scenes, Mint accesses these accounts and their data, and then crunches the numbers -- providing actionable advice back to the user.
Data aggregation is the backbone of modern financial technologyWithout data aggregation, PFM apps like Mint would require a user to manually input all his data. That’s not happening. Lending apps that judge creditworthiness by analyzing savings and checking balances across financial institutions would be dead in the water without data aggregation. Data aggregation is the backbone upon which modern financial technology is built. As we looked around, we found articles on data aggregation here and there, but no one had looked at data agg from the bottom up. The topic seemed a throwaway, leaving buyers of data agg to fend for themselves. The idea for a data aggregation buyer’s guide was born.
How to choose a data aggregation providerThere is a lot of overlap in coverage by providers. Through our research, we were surprised to learn that as much as competitors in the space vie for new clients, they also collaborate and share data among each other. But there are significant differences, ranging from how many financial institutions a data aggregation provider covers to how these firms acquire their data and price it.
Know your needsIt’s important to start researching the data aggregation field with a clear idea of what you’re trying to accomplish.
- Coverage: For your technology, do you require connection points to every banking and financial institution in your target geography? Or are you more tightly focused around customers from specific FIs?
- Pricing: Data aggregation can get quite expensive, so how data aggregation firms price their services matters. What’s your budget for data aggregation? Where’s breakeven from a cost and revenue perspective on your data aggregation efforts?
- Focus: Throughout the course of our deep-dive into the space, it became clear that data agg companies each have their own flavors. Some focus on banking data -- others on investment and brokerage data. Some try to go very broad while others achieve depth in their industries.
- Developer friendliness: This attribute is as much about your business as it is about the data aggregation firm you decide to work with. The industry has been around for more than 20 years and technologies vary when it comes to working with a modern development team. You’ll want to find a match between your firm’s capabilities and the UI/UX of the data aggregation industry. How developer friendly do you require your data agg provider to be? Is it important for what you’re trying to accomplish?