When Our Gut Feeling Turns Supervillain: Battling Bias in Investments

Investors face a relentless stream of decisions—reviewing pitch decks, evaluating financial statements, analyzing markets, assessing business models, and team dynamics. But as the day wears on and cognitive overload sets in, even the sharpest minds fall prey to decision fatigue. The result? Rushed judgments, inconsistent evaluations, and swings between undue caution and reckless risk-taking. Lurking behind these mental shortcuts is a familiar yet often overlooked challenge: bias.  

Key Takeaways 

• Bias distorts investment decisions, leading to missed opportunities, and unnecessary risks. 

• It undermines fairness and trust, reinforcing the status quo and damaging credibility. 

• Common biases include herding, confirmation, overconfidence, availability bias, and loss aversion. 

AI can help detect and reduce bias, ensuring more objective and consistent evaluations.

Understanding Bias

Bias can subtly weave its way into the investment process, often without being immediately obvious. In this high-pressure environment, investors may unknowingly favor certain business models, overlook critical red flags, or be swayed by personal preferences. These biases shape the way opportunities are evaluated and, ultimately, decisions are made. To understand just how deeply bias can influence the process, let’s take a closer look at some of the most common types and their impact on investment choices.  

Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4818073

Source: CFA Institute (survey of 724 practitioners from across the world)

Understanding the True Cost

Bias in investment decisions isn’t just an abstract ethical concern—it carries tangible consequences. When bias clouds judgment, investors risk missing out on promising opportunities simply because they don’t fit preconceived molds. This reinforces the status quo and stifles innovation. 

Beyond lost opportunities, bias can expose investors to unnecessary risks. Overlooking red flags due to affinity or confirmation bias can lead to poor decision-making, while herding bias may result in inflated valuations and unsustainable market trends.  

Fairness and equal opportunities are also at stake. A system skewed by bias ultimately undermines transparency, erodes trust, and damages an organisation’s reputation. In an industry built on credibility, being known for objective and rigorous due diligence can be a crucial competitive advantage. 

On an operational level, information overload can take a toll on teams. It can lead to decision fatigue, burnout, and even stagnation, where scaling efforts are held back. 

Strategies that will help you tackle these challenges: 

Recognizing bias is one thing—actively addressing it is another. Investors looking to make fairer, more rational decisions must take a deliberate, structured approach. Here are key strategies to mitigate bias in the investment process: 

1. Acknowledge the Possibility of Bias 
   The first step is accepting that bias exists—even among the most seasoned investors. By acknowledging this, organizations can create an environment where bias is openly discussed and proactively addressed. 

2. Evaluate Your Current Process 
   Bias often hides in plain sight. Taking a hard look at existing investment workflows can reveal unconscious patterns. Are certain founders or industries given preferential treatment? Identifying these blind spots lays the foundation for meaningful change. 

3. Leverage Technology: AI as your assistant Artificial intelligence has been hailed as a game-changer across industries, but when it comes to investment decisions, it’s important to separate hype from reality. AI is not a magic bullet. It won’t replace human expertise, nor should it. Instead, its real value lies in acting as a safeguard against cognitive blind spots—a tool that enhances judgment rather than making decisions outright. With careful calibration and oversight, AI can be deployed for what it does best—analyzing language, identifying patterns, and providing structured assessments. AI-powered tools can help grade applicant responses against pre-set benchmarks, and explain the rationale behind it. Here’s how AI-assisted grading is transforming investment evaluations:

    

   • Bringing Structure to Subjective Decisions – AI standardizes evaluations, ensuring that applicant responses are assessed against pre-set benchmarks. 

   • Detecting and Correcting Bias in Real Time – AI can identify skewed decision-making patterns and adjust weightings accordingly, helping to counteract hidden biases. 

   • Preventing Fatigue-Induced Errors – Investment decisions often happen under time pressure, leading to inconsistent judgments. AI helps flag discrepancies and maintain a more even-handed approach. 

   • Promoting Transparency and Fairness – When applied correctly, AI can create a level playing field, ensuring that all applicants—regardless of background—are evaluated on merit. Next, let’s examine how these principles come to life in a real-world case study. 

Case Study

To gauge the real impact of AI-assisted grading, we put it to the test with Rootical, a regenerative venture studio based in Uganda. The experiment was straightforward: compare manual evaluations with AI-enabled assessments across a small sample of 20 applications.

First, Rootical’s team manually reviewed and scored the applications. They also set clear grading anchors or reference points to guide AI in its evaluation process. The AI was then tasked with grading the same applications using those pre-defined benchmarks.The results were interesting. Even in this limited dataset, the AI grading system flagged two significant inconsistencies — cases where human and AI evaluators had rated responses more than two points apart. Upon manual review, AI’s assessments proved to be the more consistent and accurate reflection of the initial criteria. On the other hand, this exercise was also a key step for Rootical to further fine-tune the grading anchors.

While two inconsistencies in a set of 20 might seem minor, the implications are far-reaching. When scaled to hundreds of applications, these inconsistencies quickly compound.

At first, we were skeptical about using AI for grading — our screening process is part of our secret sauce, after all. But after testing it with Level, we saw the AI flag inconsistencies we might have missed. It didn’t make decisions for us, but it for sure helped us save a lot of time and refine our process and make selection decisions more confidently. Hannes van der Eeckhout, Founder and Director, Rootical 

So, any tools out there?

At Uncap, we developed Level to tackle this challenge head-on. Learn more about it here.

Looking to enhance your investment operations? Book a demo today.