In 2021, JPMorgan Chase & Co. paid US175 million for Frank – a platform "designed to make college more affordable for millions of Americans and help them achieve financial wellness in their lives", according to press statements at the time.
The same press stated that: “Frank currently serves more than five million students at over 6,000 higher education institutions across the country”, and that JPMorgan’s investment rationale was to tap into this market to build lifelong relationships, and a deeper engagement with students.
The problem?
Frank had fewer than 300,000 customer accounts.
The rest – at least 4.265 million – JPMorgan alleges were fake. Worse still, they were intentionally fabricated to dupe the financial giant into paying the purchase price, say court filings.
While we will have to wait to see how the courts reconcile the allegations and counter claims of this specific transaction, there is a principle here.
Increasingly, business models - and therefore business valuations - are being anchored on the quality and quantity of data. In this case, the number of unique customer accounts.
Yet very few investors are actively validating a target's data assets or investing in data due diligence proportionately to the perceived value of data.
Our generic ('red flag') data due diligence provides investors with a rich understanding of how well a company is using data to power its business and operational models, plus includes an evaluation of key components such as data sources and data quality. Vitally, this assessment also uncovers critical data risk factors to the investment thesis.
Actually, in the past few quarters, we have performed data audits in situations where data was far less critical to the investment thesis than in the case of Frank. And the investors that we are working with in these instances are increasingly asking us to expand the scope of our data assessment to include deep dives into what matters for value preservation and value creation.
We appreciate that due diligence isn’t a panacea against fraudulent misrepresentation. However, we argue that formal data due diligence elevates the commercial understanding of data’s role and impact – risks and opportunities – to the investment thesis. Plus, the process opens a deeper conversation between negotiating parties, resulting in greater awareness, alignment, and ultimately better pricing confidence.
Data due diligence is important.
After all, in today’s world, every deal is a data deal.
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