Data Aggregation – Part One of Two – Use Cases in the U.S.

Retail Investor data aggregation will be a fiercely defended, contested, and lucrative battleground as the AI wars heat up.

The AI Revolution is here - OpenAI has been a breakout product that has rapidly changed the technology landscape, shaking the foundation of Google and shifting VC funding towards AI, with investments totaling over $35.5 billion in 2021. No one can predict how the AI race will evolve, but it is certain to have leaders in each category, vertical, and medium. In the near term, the question becomes what incumbent digital players can do to protect their businesses and create a defensive moat/sustainable competitive advantage.

In the investing space, one area that will rise to the top of every AI conversation will be “data.” Data could mean stock mar- ket data, fundamental data, bond data, historical data, and so much more that comprises the financial data industry, which is valued at approximately $24 billion. In this highly competitive space, incumbents will aggressively defend their data ownership, rights, and attribution.

Another data conversation will be aggregated customer data. In the US, aggregated customer data has been a flashpoint be- tween financial institutions, aggregators, and customers for over two decades. Dating back to the “Schwab No Action Letter” in 1995, the commoditization of user data has evolved into a major industry and driven business trends globally. As AI prolif- erates this industry, we will see winners and losers in each industry, with certain attributes leading to success.

Aggregator Data:

The amount of actionable data being collected that could inform investment decisions has been overwhelming. For example, Plaid, one of the leading data aggregators, claims to have connected to more than 11,000 financial institutions and over 200 million consumer accounts. Yodlee, another major player, reports access to over 21,000 data sources and 45 million users. By leveraging AI, however, this data becomes much more accessible. Imagine an investment company able to quickly and effi- ciently analyze complete credit card spending by category to predict stock prices or a media platform able to provide specific insights of investment holdings linked to their platform?

Aggregator M&A:

Finicity, a data aggregation firm, was acquired by Mastercard for $825 million in 2020. Plaid had agreed to be acquired by Visa for $5.3 billion in 2020, but the deal fell through in 2021 due to antitrust concerns raised by the Department of Justice. Plaid’s valuation is rumored to have doubled, validating the value of its assets. We expect this interest to be just the beginning of significant M&A activity as new players emerge in the space. (We will cover the European Landscape where Tink was snapped up in another post.)

Where does it all go?

As AI continues to revolutionize the technology landscape, data aggregation will become a more and more critical aspect of the financial industry. The competition for data ownership and control will likely intensify, and the role of regulators in shap- ing the future of data access and security will be crucial.

The value of aggregated data will continue to increase, putting pressure on financial Institutions to gain access and clarify who owns the customer data. Accordingly, the value of trusted aggregators will continue to increase, and the need to safeguard their data and how it is used will be essential. With more effective ways to analyze aggregated data, customers should be look- ing to extract as much value from their aggregated data as possible to better inform investment decisions. While this financial data is being used selectively by sophisticated investors, as yet it has not materialized broadly in a widely available format.

We at Joffre are closely following this space as we look to identify new defensible technologies as they emerge. Stay tuned for part 2 of this series on data aggregation, which will focus on the landscape in Europe.