Due diligence and finding the next tech unicorns

‘Tech unicorns’ come in many colours, but their financial strategy is cloudy. Examining some tech unicorn failures reveals why up-to-date data can make due diligence as easy as ABC…

Nobody has topped venture capitalist Aileen Lee’s vivid 2013 description of a $1bn+ startup company as a unicorn. It’s a fairytale concept, and yet astonishingly, as of February 2023, there are in excess of 1,200 unicorn companies listed worldwide. Understandably, they’ve been a magnet for investors, with a myriad of column inches devoted to their stories.

However, in some notable boom and bust cases, the publicity morphed into goldfish-bowl documentaries, such as WeWork: Or the Making and Breaking of a $47 Billion Unicorn. Even more unflattering was the lengthy eight-episode drama The Dropout, minutely detailing the rise and fall of Elizabeth Holmes’ company Theranos. The number one take-home was the unquestioning belief in the failed unicorns’ self-assessed value and viability.

Such headline-attracting melodrama has done nothing for the current widespread perception of the unicorn startup, but what does the bigger picture look like? At the end of January, Forbes were keen to fill us in. Accompanying a cartoon of a hospitalised unicorn, former Big Four financial statement auditor Matt Durot detailed the woes of 44 startup founders who are now “nearly £100 billion poorer than they were a year ago”.

Add to this the influential US Securities and Exchange Commission’s objection to unicorns’ lack of transparency about their shareholder structures, due to their status as private, unlisted companies, and you have the resulting mix of government suspicion and investor wariness brought into the equation.

Even at the end of 2018, when summing up the demise of Theranos, Mary Juetten, attorney and founder/CEO of Traklight, gave the following warning: “It’s vital that entrepreneurs believe in themselves and their ideas, but that belief and drive are best paired with advisors willing to speak the truth, even when it might be painful, and a willingness to admit mistakes, shortcomings and even defeat. Honesty goes a long way in avoiding a myriad of potential startup problems.”

It’s a nice sentiment, but can investors and business relationships really rely on this level of honesty, when a CEO is heavily entrenched in the success of their enterprise?

This seems naive when you study CBInsights report that amongst 252 startup horror stories, e-commerce platform Nice Tuan was a prime offender in misleading potential investors and business contacts. The article detailed that “goods were sold at below cost to entice customers”, and “fake buyers appeared at the end of each month to meet sales targets”. Sales targets, incidentally, which Nice Tuan estimated to be 80 billion Yuan per month – in reality they barely achieved two million Yuan in the same time frame. On top of that, the company was fined 1.5 million Yuan for ‘fraud’, ‘dumping’ and ‘misleading advertising’.

It’s no wonder that unicorns cannot be valued on the reassurances of their CEOs alone.

Understanding all of this is the key to finding a solution which not only informs, but also enables strategically intelligent investment and business relationships. It simultaneously reveals how mnAi and AI-assisted analysis can be used to better identify the startups with genuine market potential.

From new suppliers to financial checks, undertaking comprehensive due diligence is an essential part of everyday business life. mnAi collates millions of data points on active UK companies. With in-depth analysis on hard-to-find data points, which identify potentially damaging or beneficial hidden director networks, advanced financials, debt, investments, and more, mnAi offers invaluable tools that support the due diligence process.

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