How Venture Capital Could Use Large Language Models to Screen Sustainability Impact Startups

This study investigates the potential of large language models (LLMs), such as ChatGPT, to aid venture capitalists in the screening of startups that maximize sustainability impact. To determine the scope that maximizes impact for venture capitalists' and to identify effective screening criteria, the study utilized theoretical research and interviews. The thesis suggests that the ideal investment space is investments into high-risk, software-centric companies contributing to a sustainable system change that maximizes outcome impact instead of optimizing for environmental, social and governance metrics. This investment space along with other defined critical success factors were then deployed in an effort to test LLMs' efficacy in targeting companies maximizing impact. Two prompting techniques were trialed, one question-based prompt where questions on critical startup success factors were asked, and another using a comparative method where the characteristics of screened startups were matched with investor profile preferences. In both versions of the model, the provision of context proved indispensable to analyze relevant startups, given GPT-4’s knowledge cut-off in 2021. Without context, the LLM often could not provide an answer or provided an imaginary one, especially for younger startups. The question-based prompting could accurately address some specific questions, while the investor profile prompt showed the most promising results by being able to efficiently summarize and present relevant output text on the given areas of interest. It was also found that the quality of the data input in the model directly affects its efficacy and it is therefore necessary to pick data carefully to avoid biases and greenwashing. This was especially true for question-based prompting, since the investor profile prompt was better at conducting an overall assessment of the companies with scarce information, but did still struggle to produce insightful ratings. In terms of the specifi
How Venture Capital Can Unleash the Power of ChatGPT to Create a Sustainable Future If you had 100 million dollars, how would you invest to create the most positive impact on society and the environment? Venture capital is frequently brought up as a driving force of systematic change in society and the investing form that can create the biggest impact. Yet, the integration of sustainability in venture capital has until recently largely been overlooked, only now are firms starting to recognize its potential. With the introduction of OpenAI’s revolutionary model ChatGPT, the things we thought were possible to achieve with artificial intelligence were propelled to another level. ChatGPT already has broad applications, spanning from code generation and essay writing to even aiding investment decisions. We propose that with the help of ChatGPT, venture capital firms can finally embrace sustainability as an integral part of their business model, helping them to identify startups that maximize impact. Undoubtedly, investing in sustainable companies is paramount for solving the world’s social and environmental crisis. Venture capitalists’ (VCs) unique strategy, inclination towards short-term investments in high-growth ventures, has traditionally posed challenges for VCs incorporating impact investing. This is due to capital-intensive, long-term investments such as solar cells being on top of the sustainability agenda. By leveraging their existing capabilities to support high-risk, software-centric companies that drive sustainable system change, we argue that VCs can carve out a new, more appropriate space within impact investing. This novel and specific investing scope, requires a more sophisticated screening process than what is in place today. By harnessing the power of ChatGPT, our hypothesis was that VCs could refine and improve their way of identifying high-potential startups, and in turn find hidden gems in the impact space. To test our hypothesis, we performed a stud