In this post I continue the fintech market map deep dive video series. In part 6, I explore another infrastructure segment - data aggregation & normalization. I try to highlight some of the nuances and exciting trends in this space. Click on the video for the full take and check out the highlights below.
What is it?
Data aggregation and normalization infrastructure companies connect into a sector of businesses and make their user data accessible via API to their customers. Some examples include banking data that's been most famously affiliated with Plaid. Others include payroll and accounting, to name a few. This could be consumer data like banking balances or transaction histories, or it could be business P&L or accounting data.
A hot take
As you know, I'm a big believer in the need for more fintech infrastructure to make building in this space easier. This category in particular has really taken that to heart. There's been a ton of exciting innovation and startup activity, but now there are so many companies in each sub segment doing really similar things and I think we're going to see significant consolidation in the coming year or two.
Prediction for the winner in the space
Some companies in this sector have built direct connections with the businesses they are pulling data from - banks, payroll providers, etc. The reality is that the vast majority of them have not, either because of the time investment or because these vendors don't want to allow it. That means there's often a fair amount of screen scraping and other kinds of “automagical” activity happening behind the scenes to successfully retrieve the data. If these connections break frequently or the companies do not have broad coverage of providers, it's likely not worth using. Companies that are going to win need the breadth and depth required, otherwise the user experience will suffer.
Companies on the rise
Rutter is pulling business e-commerce and accounting data, Column Tax is doing that for consumer tax, and Nova Credit is focused on immigrants to the U.S. and their international information.
What am I most excited about?
I'm excited for this paradigm to be applied to other large and broad use cases, particularly for B2B. I've been obsessed with this idea of B2B data and companies that are finding interesting and relevant data on businesses and offering it up to their customers in a digestible, easy to use way.
What do you want to see?
I’d like for more industries to accept the data aggregation normalization is good for the ecosystem and for them to enable direct connections into their products. Easier access and better data helps everyone in many ways; it even drives relevance and stickiness for the companies providing that data at the end of the day. It may mean that it's driving down revenue for a specific workstream, but overall I'm a strong believer that more connections into a company are going to create more opportunity for monetization in the long term. I think we've seen that with banking and we'll continue to see it in other industries.
Check out the previous episodes if you haven’t yet:
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Data Aggregation & Normalization Infrastructure (Video Series Part 6)