PitchBook Launches an AI Tool to Predict the Next Big Startups

PitchBook has recently launched VC Exit Predictor, an algorithm-based tool that claims to predict the success of a start-up, according to a report by TechCrunch.

It is reported to generate a score on the likelihood of the company being acquired, going public, or not exiting due to bankruptcy or becoming self-sustaining.

VC Exit Predictor

McKinley McGinn, product manager of market intelligence at PitchBook, told TechCrunch that the tool was created using a proprietary machine learning algorithm, which was trained exclusively on data available within the PitchBook platform, including deal activity, active investors, and company details.

To ensure the accuracy of predictions, the tool is used for venture-backed companies that have received at least two rounds of venture financing deals.

Although PitchBook is not the first to develop such an algorithmic tool, investors have been using AI-driven platforms for years to make investment decisions. VC firms such as SignalFire, EQT Ventures, and Nauta Capital have been using AI-powered platforms to identify potential top firms, as noted by TechCrunch.

In 2021, a team of researchers also built a tool similar to VC Exit Predictor, which used public CrunchBase data to predict whether startups will exit through an IPO or acquisition, remain private, or fail.

According to McGinn, PitchBook back-tested VC Exit Predictor on a historical set of companies with known exits, such as Blockchain.com, Revolut, and Bitso. The tool was reportedly 74% accurate on average in predicting a successful exit across the set.

VC Exit Predictor could be used by venture capitalists searching for a data-driven approach for their initial evaluation of a venture-backed company.

However, the tool may also be useful for industry players seeking upcoming IPO candidates, monitoring market competitors, or looking for validation for their next investment round, according to McGinn.

Question of Resilience

Using algorithmic tools raises questions regarding their resilience to black swan occurrences like pandemics, international conflicts, and natural disasters.

"There are limitations at the market-level predictions that the algorithm can make," McGinn said in a statement.

"Since it's reliant on timely updates in a slower moving market space, it takes time for the model to adjust to rising or failing segments."

The question is whether VC Exit Predictor can predict the outcomes of such events accurately. Nonetheless, PitchBook believes that VC Exit Predictor is valuable for investors looking for data-driven approaches to make informed investment decisions.