Can AI pick the best startup investment? The next unicorn?
We all wish we could pick investments better, right? And if you’re a venture capitalist or in private equity doing so is your job. But how to know which startups will be the next Airbnb, Uber or Meta? How to tell?
Some platforms are now introducing AI-leveraged solutions to do just that: give an investor a strong indication whether or not an early-stage company is going to receive future rounds of funding and grow into that next billion-dollar unicorn. And do it with 95 percent accuracy to boot. Is this just fantasy?
Crunchbase Launches A New AI Platform To Help Find The Next Unicorn
Not according to the team at Crunchbase. Last week, the company – known for providing historical data on tens of thousands of early stage firms to its subscribers – relaunched itself as a new platform that will take this data, learn from it and then make predictions for its subscribers.
“The historical data industry as we know it is dead,” said Jager McConnell, CEO of Crunchbase, in an interview with VentureBeat. “If you are a company, a data company, and all you’re dealing with is historical data…I think you’re going to find that you don’t use it as much anymore in the future.”
Crunchbase says that its predictions will identify – with as much as 99 percent confidence – which companies that will be able to raise future funding, using a combination of private, public and “user engagement pattern” data. Crunchbase’s new AI platform will answer questions like “what is the business model of this startup?” and “compare startup A with startup B.”
“The real magic behind our ability to predict key milestones in company lifecycles lies in our unparalleled breadth and depth of knowledge,” Megh Gautam, Crunchbase’s chief product officer said. “We’ve built features that are generalized, not tuned to any single dataset.”
But Crunchbase is not the only firm doing this.
Other Platforms Are Jumping Into The AI Investment Game
Research service Morningstar has released its generative AI platform targeted at asset and wealth managers that can “process natural-language queries, read and understand hundreds of thousands of reports written by Morningstar’s analysts, gather investment information from Morningstar’s comprehensive databases, and then generate actionable, verifiable insights. Clients receive the answers they seek in seconds while getting time back to invest in higher-value activities. Clients can also layer their personal research, editorial, or support content to curate the platform’s responses.”
A stock picking AI platform called Sentieo combines financial research, data management, and analytics in one platform and allows its clients to track companies, analyze market trends, and export data efficiently for further analysis.
“Portfolio managers can search through earnings call transcripts, SEC filings, and other financial documents to quickly spot trends, sentiment, and red flags,” the company says on its website and “with its deep document search capabilities and visual analysis tools, analysts can gain insights from unstructured data, enhancing decision-making stock selection and risk management.”
Another platform called FinChat.io says it can “help quants with deep data analysis, market prediction models, and financial modeling, enhancing their ability to develop algorithmic trading strategies” all through its AI-leveraged tools.
Even OpenAI is in the game with ChatGPT 4. The company says that GPT-4 “excels in analyzing market trends and predicting investment outcomes. It is particularly effective for generating insights from vast datasets and automating trading decisions.”
Although none – other than Crunchbase – of these platforms are claiming that they can always make predictions for picking investments – let alone with a 95 percent accuracy – these deliverables don’t seem far off. For now most investment platforms are providing research using GenAI. But, we can see where this is going. As these platforms become better trained and therefore smarter, many investment decisions will be made by algorithms without any human involvement. A lot of this already being done with government bonds and stocks by mutual fund managers and larger Wall Street investment funds on behalf of their retail customers.
These tools will be used in conjunction with human investment analysts and serve as another, expert voice in the decision making process. They will do the grunt work – the research and number crunching – currently being performed by lower level workers and will ultimately replace a number of them.
But they won’t completely replace humans in the investment process.
That’s because startup companies are run by humans. And a significant part of any VC’s investment decision is not just the product, or the model, or the potential for scale up and exit, but who is actually running the company and does this person have the necessary personality traits for ensuring their return on investment? Without looking in that person’s eyes and spending hours in a conference room, on a golf course or at a bar, it’s impossible to truly understand the person – or people – who’s being backed.
One thing’s for sure: no matter how good AI gets at data analysis, it’ll likely never reach that level of human judgment. So will AI pick the next startup investment? At most it will contribute to the process.
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