From Open Banking to Data-Driven Mergers: The Hidden Power of Consumer Financial Data

In partnership with

Linda Jeng is the Founder & CEO of Digital Self Labs, a research fellow at Georgetown Law and the Bank for International Settlements, and editor of Open Banking (Oxford University Press). She was a former senior official at the U.S. Treasury, Federal Reserve Board, and Financial Stability Board.

The Missing Chapter

I had the privilege of editing Open Banking — the first academic book on this important subject. This book, published by Oxford University Press, covered everything from data portability and consent to application programming interfaces (APIs) and interoperability. But one question kept echoing in my mind, until I realized that I was missing a chapter.¹

What happens when the very consumer data that open banking unlocks starts flowing across corporate boundaries — through mergers and acquisitions?

That question became the spark for what is now a Bank for International Settlements (BIS) Working Paper: “Consumer Financial Data and Non-horizontal Mergers,” co-authored with Jon Frost, Elisabeth Noble, and Chris Brummer.² The paper will soon appear in the Fordham Journal of Corporate and Financial Law.³

Our research provides an urgent — if partial — answer: how your data is used following mergers could well be one of the most consequential issues in the new digital economy. It’s critical that policymakers turn their focus to this least examined aspect of our data-driven world.

When Data Became the New Vertical Integration

For decades, competition law has focused on horizontal mergers — the combination of two direct competitors. Regulators know how to measure those: market shares, concentration ratios, prices.

But digital finance isn’t about factories and output anymore. It’s about data flows and predictive power.

When a payments platform merges with a data aggregator, or a lender merges with a credit bureau, the key question isn’t “how big is their market share?” It’s “who now controls the most complete picture of the consumer?”

That’s a non-horizontal merger — one that connects firms at different layers of the value chain. In a data-driven world, those layers are no longer production layers — they’re data layers.

The “Aha” Moment: Visa and Plaid

The idea clicked for me when Visa announced it would acquire Plaid. Plaid is the connective tissue of U.S. open banking — linking consumers’ bank accounts to apps like Venmo and Robinhood. Visa, meanwhile, is a dominant player in global payments infrastructure.

The U.S. Department of Justice sued to block the merger, arguing that it would “eliminate nascent competition.” (They had a smoking gun — er, volcano — in the form of internal communication from Visa’s CEO stating that they were trying to do just that.⁴ ) The case never went to trial — the companies walked away from the deal, and Plaid completed a massive fundraising round and operates independently to this day.

Perhaps because there was a smoking gun, the case never needed to grapple with the issue of combined data power. While at first glance the merger looked like a normal fintech acquisition, examined through the lens of data, it is perhaps better seen as an information acquisition.

Visa wasn’t just buying a company. It was buying visibility into how millions of people spend, save, and transact. While privacy laws and terms and conditions may have limited Visa’s ability to do this, the core issue is relevant for many cases beyond this one. Open banking and competition law are about to collide — and we don’t yet have the tools to make sense of it.

How Control over Consumer Financial Data Changes Mergers

Traditional merger tests rely on metrics like the Herfindahl-Hirschman Index (HHI) — a measure of market concentration. But in data-driven markets, concentration isn’t the only problem. The real leverage comes from data complementarities — the ability to combine datasets that make each other more valuable.

Imagine if one firm holds bank account cash flow data, another holds credit and debit card transactions history, and another holds location or behavioral data. Individually, each dataset offers a partial picture. Together, they create an almost omniscient view of the consumer.

That’s predictive power — and predictive power is the new market superpower.

From Supply Chains to Data Chains

Think of traditional mergers as integrating supply chains. Now, think of modern digital mergers as integrating data chains. 

Mastercard’s acquisition of Finicity. American Express’s acquisition of Kabbage. These weren’t just about expanding into new business lines. They were about consolidating the pipes of consumer financial data — who can access it, analyze it, and build predictive models on top of it.

In each case, the merged firm’s competitive edge came not from producing more, but from knowing more.

Rethinking Merger Policy for the Data Era

Competition law needs a new toolkit — one that reflects how data actually drives market power today. Three updates are now essential:

1. Treat data as a core input to competition. Data is to digital markets what energy was to industrial ones — a foundational input that determines who can compete. That means expanding merger review beyond price effects. Data concentration can stifle innovation and entry, even when prices don’t change.

2. Measure data complementarities, not just market shares. Combining complementary datasets can create synergies that traditional concentration metrics miss. This measurement will require deeper interagency collaboration. Competition authorities, financial regulators, and privacy agencies must share analytical frameworks.

3. Use open banking principles as competition remedies. Data portability, interoperability, mandated data access, and functional separation — which open banking has already pioneered — could also mitigate data-driven concentration and prevent foreclosure effects.

4. Recognize data governance as market structure. Who holds data — and under what terms — shapes the entire financial ecosystem.

Next Steps

When I first began putting together the Open Banking book, the focus was on data as empowerment — helping consumers move their data, choose their providers, and unlock innovation.

Through this research, I’ve come to appreciate the flip side: data as power — how its concentration can tilt markets, reinforce incumbency, and reshape competition itself.

The next generation of financial competition won’t be fought over branches or fees. It’ll be fought over data access and data control. To monitor that fight, we need:

• Quantitative tools to evaluate data synergies — metrics for complementarity, substitutability, and predictive overlap.
  

• Empirical maps of where financial data sits in the value chain.
  

• And cross-disciplinary teams — economists, technologists, and lawyers — working together to redefine what market power means in the age of algorithms.

The question we face now isn’t just how to open up financial data, but how to prevent data from being re-closed through consolidation. In an era of predictive finance powered by AI, the firms that know the most about us can shape who gets credit, at what price, and under what conditions. That’s why understanding the merger implications of consumer financial data isn’t just academic — it’s vital for a fair, innovative, and open financial system.

The opinions shared in this article are the author’s own and do not reflect the views of any organization they are affiliated with.

^[1] Jeng, Linda, ed., Open Banking (Oxford University Press 2022); available at: https://doi.org/10.1093/oso/9780197582879.001.0001

^[2] Jeng, Linda, et al. “Consumer Financial Data and Non-Horizontal Mergers.” The Bank for International Settlements, 19 Mar. 2025, www.bis.org/publ/work1251.htm.

^[3] Linda Jeng et al., Consumer Financial Data and Non-Horizontal Mergers, 30 Fordham J. Corp. & Fin. L. 1 (2025)

^[4]  Justice Department Sues to Block Visa’s Proposed Acquisition of Plaid

Open Banker curates and shares policy perspectives in the evolving landscape of financial services for free.

If an idea matters, you’ll find it here. If you find an idea here, it matters. 

Interested in contributing to Open Banker? Send us an email at [email protected].

Stop Digital Shoplifters Before They Drain Your Profits

"Digital shoplifting" sneaks in after payment, costing stores shipping, revenue, and chargebacks. Chargeflow Prevent stops it before fulfillment. Free for your first 1,000 transactions.

Stop Fraud in Its Tracks