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SEATTLE, March 20, 2023 ~ PitchBook, a leading data provider for the private and public equity markets, has released its VC Exit Predictor, a new tool and scoring methodology that objectively assesses a startup's prospect of a successful exit. The tool leverages machine learning and PitchBook's database of information on VC companies, financing rounds and investors.
The primary component underpinning the tool is a classification model developed by PitchBook's Institutional Research Group that predicts the probability a VC-backed startup will ultimately be acquired, go public, or not exit due to failure or becoming self-sustaining. The release comes at a time when the liquidity available for VC-backed exits has fallen sharply in recent quarters, and the outlook for improvement remains bleak.
The new tool empowers investors and founders to prioritize and advocate for the right opportunities, while streamlining decision-making and due diligence processes. For a company to have an exit prediction, it must be currently VC-backed with at least two rounds of venture financing. The tool uses PitchBook's robust dataset to generate exit predictions and the following areas are examples of data points leveraged: company details such as patents, industry, employee count, news coverage, number of acquisitions; deal activity such as maturity, fundraising frequency, average deal size; active investors such as investor track record, number of crossover investors and number of investors.
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After training the model on 46,000 observations from startups with known outcomes, PitchBook tested the algorithm on more than 11,000 out-of-sample observations and accurately predicted success (M&A and IPO) versus no exit outcomes at a rate of 75%. McKinley McGinn Product Manager at PitchBook said "In the last 10 years an influx of capital and institutional investor interest has led to an explosion in the number of VC-backed companies which has made sifting through the data to identify investment opportunities more challenging and time consuming. With PitchBook's VC Exit Predictor investors will be able to understand a company's trajectory better and engage in a more rigorous decision making process by eliminating biases and improving how they evaluate risks associated to investments. Users can digest a large sum of data on these companies in much faster timeframe enabling smarter dealmaking"
PitchBook's Institutional Research Group published Gaining an Edge in VC Investment Selection alongside today's launch which delves into how PitchBook's VC Exit Predictor can be used to improve investment selection process. To mitigate affects from depressed exit environment this tool is expected to help maximize shareholder value while decreasing demand for new fundraising by providing liquidity for VC backed exits.
The primary component underpinning the tool is a classification model developed by PitchBook's Institutional Research Group that predicts the probability a VC-backed startup will ultimately be acquired, go public, or not exit due to failure or becoming self-sustaining. The release comes at a time when the liquidity available for VC-backed exits has fallen sharply in recent quarters, and the outlook for improvement remains bleak.
The new tool empowers investors and founders to prioritize and advocate for the right opportunities, while streamlining decision-making and due diligence processes. For a company to have an exit prediction, it must be currently VC-backed with at least two rounds of venture financing. The tool uses PitchBook's robust dataset to generate exit predictions and the following areas are examples of data points leveraged: company details such as patents, industry, employee count, news coverage, number of acquisitions; deal activity such as maturity, fundraising frequency, average deal size; active investors such as investor track record, number of crossover investors and number of investors.
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After training the model on 46,000 observations from startups with known outcomes, PitchBook tested the algorithm on more than 11,000 out-of-sample observations and accurately predicted success (M&A and IPO) versus no exit outcomes at a rate of 75%. McKinley McGinn Product Manager at PitchBook said "In the last 10 years an influx of capital and institutional investor interest has led to an explosion in the number of VC-backed companies which has made sifting through the data to identify investment opportunities more challenging and time consuming. With PitchBook's VC Exit Predictor investors will be able to understand a company's trajectory better and engage in a more rigorous decision making process by eliminating biases and improving how they evaluate risks associated to investments. Users can digest a large sum of data on these companies in much faster timeframe enabling smarter dealmaking"
PitchBook's Institutional Research Group published Gaining an Edge in VC Investment Selection alongside today's launch which delves into how PitchBook's VC Exit Predictor can be used to improve investment selection process. To mitigate affects from depressed exit environment this tool is expected to help maximize shareholder value while decreasing demand for new fundraising by providing liquidity for VC backed exits.
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