When we created Fundr, we set out to create a platform that would combine the power of AI and portfolio diversification to eliminate investor bias. But what is investor bias, and why does it need to be addressed?
In 2020, Harvard Business Review (HBR) built an investment algorithm and compared the algorithm’s evaluation of startup businesses with the returns from 225 angel investors over 623 deals. As we covered in The Future is Here: Using AI for Startup Investment, the algorithm gained a 184 percent higher internal rate of return (IRR) than the angel investors. 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 that investors bring to the evaluation of startups. These biases, defined by HBR, include:
Local bias, which describes angel investors’ tendency to make investments that are in close geographic proximity to themselves
Loss aversion, meaning angel investors’ tendency to be more sensitive to potential losses than to potential gains
Overconfidence, when investors “overcommitted” and spent significantly more money on one startup that they usually would
While these biases are usually unconscious and unintentional, their impact is widespread. A review of venture capital investments from 2013 to 2017 found that women led just 9.2 percent of the startups that received money from 135 of the largest venture capital firms. Less than 2 percent of funded startups had a Latinx founder, and 1 percent was led by a Black person. In a review of 2020 investments, Crunchbase reports that Black-owned U.S. startups received $1 billion in venture funding during 2020, while Latinx-owned companies received $2.7 billion — just 0.6 percent and 1.7 percent, respectively, of a total pool of $161.4 billion.
At every step of the investment process, research is uncovering instances of unconscious investor bias.
DocSend, a Dropbox subsidiary, found that venture capital firms even perpetuate biases in pitch deck review processes. Investors spent 18 percent more time viewing pitch decks from all-male teams than those made up of only women. When reviewing the decks, investors spent more time on fundraising and product slides submitted by white male teams, while focusing on business model and market traction slides of all-female teams, suggesting that investors are more uncertain about female-led business models than male-led models. The result? Male-led businesses raised 70 percent more than women did in 2020.
And it’s not just pitch decks. In 2014, the Harvard Kennedy School discovered that when investors were presented with the same recorded pitch - same slides, same content - pitches narrated by men significantly outperformed those voiced by women. In 2017, HBR found that male and female founders get asked different types of questions - men were more frequently asked questions that are considered “promotion” questions, focused on future planning, achievement, and hopes (e.g. “How do you plan to monetize this?”). Female entrepreneurs were asked what are considered “prevention” questions, or questions that are focused on safety and vigilance (e.g. “How long will it take you to break even?”).
The biases most frequently reported on are around gender and race, but other implicit, unconscious biases come into play regularly, like age bias, pattern matching, and what’s known as the ‘curse of knowledge.’ Most humans regularly make decisions that are influenced by 12 of the most common cognitive biases - everyone does it. While not intended to cause harm, in the startup sector, these biases can prevent some entrepreneurs from getting funding for their business ideas, and can prevent investors from finding the next great investment and significant ROI.
To help combat this bias, Fundr’s platform provides investors with 90 separate pieces of data to support due diligence - data points for everything from team, to market, traction, to information on the founders. By quantifying the due diligence process, Fundr aims to remove some of the subjective bias that too often holds investors back from making investment decisions with large potential returns. By eliminating investor bias in startup investment decision-making, we are working to help every founder get funding to build their scalable business, and helping every investor to get access to those businesses and maximize their ROI.