FTX, Theranos – What is the role of data in due diligence?

“Due diligence once meant sending bankers to check that a mining company really had a working gold mine, hiring accountants to scour the books and asking lawyers to identify contracts that could prove troublesome in a bankruptcy. These days, it is hard to know what due diligence actually means.” – FT Article


FT just published a scalding article questioning due diligence in the face of high profile crash-and-burn deals: FTX, Theranos, and most recently BlockFi.


I have seen some companies (not ones I have worked for!) conduct due diligence by regurgitating what the management team has said over Zoom meetings.  In some cases, some teams have taken management spreadsheets, reformat them, and call it a day.  Minimal checks, and certainly no scouring.


In the pursuit of helping clients close deals, due diligence efforts can be pressured to focus on the positives – what is growing, how to create opportunity for change if there are negatives.  No one likes to say that they spent thousands of dollars just to uncover a dud. Where is the financial incentives in that? Private equity and venture capital are long-only and don’t have a short engine to monetize finding frauds and failures directly.

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Management team: “The house is made of bricks” .

In the end, this issue boils down to culture and approach.  Is there a culture of truth or sales?  Is the methodology sufficient to uncover the underlying truth, or does the process merely repackage the management story?


The article recommends delving into the way companies spend money for each transaction, looking for oddities such as in the case of FTX.  I would go one step further and say that transaction level analysis should cover not just cost but also revenue sources.  While Big Data and data science may not identify all problems, such as BlockFi, this approach would reveal true unit economics as in the case of Theranos.  Only by verifying each moving piece can one ascertain whether the company is built on solid fundamentals or like a house of cards.


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Joseph Davin

Joseph Davin is Founder and Managing Partner of Davin AI. He was Head of Data Science at Two Six Capital and West Monroe Partners. He received his PhD in Marketing from Harvard Business School, is a Senior Fellow at Wharton Customer Analytics, and teaches at Cornell Tech.