.png){kind=small}
Right now, venture capital investors use AI for only about 5 percent of investment decisions, but by 2025, it’s expected that the use of AI will grow exponentially, fueling a full 75 percent of venture investment decisions. AI is already behind innovative and disruptive opportunities in healthcare, financial services, agriculture, and manufacturing. The World Economic Forum calls AI the driver of the Fourth Industrial Revolution. The startup investment ecosystem is ripe for the change that AI can bring when applied to funding decisions. Investors, researchers, and economists have used AI to inform their investment decisions and have seen impressive returns despite the long-held notion that early stage investment is a personal, feelings-based decision.
In 2017, Social Capital introduced capital-as-service, a new way to invest in early-stage startups. The firm was created to provide a data-driven way to support investment decisions. By crunching key data points about a business’ revenue, engagement, and growth opportunities, the platform allowed Social Capital to quickly invest or to pass on the opportunity, while providing key feedback to founders. In a private beta test, the platform evaluated 3,000 companies and committed to invest in several dozen companies across 12 countries - without having a single venture pitch. The returns speak for themselves - Social Capital consistently saw returns higher than the average venture capital firm. Using the strength of data, Social Capital also found that it was investing in successful organizations with diverse CEO demographics - a rarity in venture capital funding. 42 percent of the companies Social Capital funded had a female CEO, and the majority of CEOs identified as non-white. For comparison, at that time, female founders were only receiving 21 percent of venture capital funding.
In 2018, John Sibley Butler of Texas Venture Labs published the results of his work testing how AI machine learning could be used to predict the success of startup business plans. He tested 19 business plans - 10 from Silicon Valley and nine from Austin - using an assessment platform called PredictionWorks which was powered by AI and startup business investment data. In the experiment, the platform was not permitted to use any information from any source after the date of a company’s business plan submission. It was also not allowed to have any contact with a company’s customers, vendors, or management team. The companies evaluated were required to have complete business plans, and be venture- or angel-backed. The goal was to learn if the AI could successfully identify those companies that would earn a high ROI-based IPO or sale/merger liquidity event within seven years of launching. The model correctly assessed 100 percent of the business plans from Silicon Valley startups, and 90 percent of those in Austin by forecasting the seven-year investment returns for the start-ups capitalized through venture capital and angel investors.
In 2020, Harvard Business Review (HBR) built an investment algorithm and compared its evaluation of startup businesses with the returns from 225 angel investors. Using machine learning, the algorithm was created to evaluate the potential survival of the startups involved in 623 deals across one of Europe’s largest angel investment networks. The algorithm used the same data available to the human investors, and it received an internal rate of return of 7.26 percent, compared to the human investors’ return of 2.56 percent - an increase of 184 percent. In particular, the algorithm easily outperformed novice investors, defined as investors who have been investing for fewer than 10 years. HBR attributes this gap to cognitive biases investors bring to the evaluation of startups.
And in 2020, we used Fundr to successfully predict the winner of an international pitch competition. All six finalists, chosen by the human review team, had a top-ten Fundr Score™ evaluated by crunching the key metrics and information supplied by founders. In the final test, all six finalists pitched their business to a panel of seasoned investors blind to the Fundr results. The winner had the highest Fundr Score™ of all entries. Fundr had correctly predicted the winner in 15 minutes.
The implications of these recent tests of AI are huge. The use of AI in startup investment is exploding for all the same reasons that we built Fundr on our proprietary AI platform. Using the Fundr platform also helps investors reduce administrative review time by 80 percent. The use of AI creates opportunities to streamline the investment process because investors can move away from guesswork,and bias, and instead surface the best companies they may have overlooked. Founders can spend more time building their business instead of building pitch decks. The time saved on both sides can be used to deepen relationships and find new, quality investments. And beyond the AI, Fundr’s platform supports long-term investment management - everything from monthly reporting to managing convertible notes.
The future is here. Join us to be on the cusp of the incredible possibilities AI creates for startup investors and founders:www.fundr.ai