The world of finance is undergoing a transformation, driven by the growing interest in impact investing – a strategy that seeks not only financial returns but also positive social and environmental outcomes. As this field expands, so does the need for accurate and comprehensive data to assess the impact of investments. Can artificial intelligence (AI) be the game-changer that helps investors make more informed decisions and combat issues like greenwashing? This article explores different perspectives on the role of AI in impact investing.
The think-tank’s perspective
Planet Tracker, a non-profit financial think tank, is on a mission to catalyze a significant transformation in global financial activities by 2030. Leveraging natural language processing (NLP), a subset of AI, the think tank recently released a report titled ‘Exposing Plastic Risk.’ This report analyzed a staggering 8,245 documents and transcripts to understand how companies in the plastic industry perceive risk.
John Willis, Director of Research at Planet Tracker, underscores that training AI algorithms to interpret text accurately is a substantial endeavor. It’s not a simple plug-and-play solution. Manual checking of NLP outputs was required to enhance algorithm accuracy. Willis emphasizes that AI-generated data must undergo rigorous scrutiny, as regulators are unlikely to provide exceptions for misleading information. However, he believes that AI can empower impact investors to compare strategies and identify best practices.
Willis also envisions AI’s potential for examining datasets to uncover insights into fund performance using deep learning and neural networks. Moreover, AI could play a crucial role in cross-checking documents for inconsistencies, such as exposing greenwashing practices in sustainability claims.
The ‘Tech Bros’ view: permutable AI
Permutable AI, led by CEO Wilson Chan, shares the vision of combating greenwashing in impact investing. Their approach centers on using large language models like BERT for detailed classification and improved accuracy in evaluating corporate commitments to sustainability and social and environmental impact.
Addressing concerns about AI’s propensity for “hallucination,” Permutable AI emphasizes the importance of backing all data with source links to ensure reliability. Their data models encompass around 27,000 suppliers worldwide and extend to social media analysis, cross-referencing data with reputable sources like the Science Based Targets initiative and the Green Cross.
Collaboration with regulatory bodies and industry organizations, such as the Global Financial Innovation Network (GFIN), and working with governments to enhance carbon emissions analysis in supply chains, highlights the commitment to eliminating greenwashing. Chan emphasizes the need for a standardized global framework matched with AI to eradicate greenwashing effectively.
The fund manager’s angle
LeapFrog, an impact investment firm, may not specifically use AI to combat impact washing, but it recognizes its potential in verifying company data against external sources in complex supply chain scenarios. They extract data from portfolio companies to monitor and track impact, and as data complexity increases, they explore AI’s utilization.
Daniel Stacey, Head of External Affairs at LeapFrog, acknowledges AI’s power in helping their portfolio companies pursue impact and improve the cost, relevance, and convenience of their products. However, he emphasizes the importance of ethical AI deployment, considering potential negative side effects, such as biased algorithms and pricing models.
Stacey also highlights the underexplored positive uses of AI in impact investing. Some companies in LeapFrog’s portfolio utilize AI to underwrite loans or offer automated customer service via platforms like WhatsApp, serving low-income customers who previously lacked access to such services.
AI is poised to reshape the landscape of impact investing. Think tanks like Planet Tracker see AI as a tool to scrutinize corporate claims and uncover inconsistencies, potentially curbing greenwashing. Innovators like Permutable AI are leveraging advanced language models to ensure the accuracy of sustainability and impact assessments. Fund managers, including LeapFrog, recognize AI’s potential for verifying data and improving the cost-effectiveness of impact-focused businesses.
However, the adoption of AI in impact investing also brings ethical and regulatory challenges. Establishing standardized frameworks and guardrails for AI deployment, especially concerning vulnerable populations, is crucial. As impact investors navigate this transformative technology, they must balance its potential for positive outcomes with the responsibility to mitigate potential risks. Ultimately, the future of AI in impact investing holds the promise of delivering growth, scale, and improved relevance while ensuring that ethical considerations remain at the forefront of decision-making.
