“Generative AI is the key to solving some of the world’s biggest problems, such as climate change, poverty, and disease. It has the potential to make the world a better place for everyone.” Mark Zuckerberg
Abstract: This chapter explores the transformative potential of Generative AI (GenAI) for addressing the increasing complexities of sustainability data analysis within fintech. It begins by outlining how the emphasis on sustainability creates a labyrinth of data, reporting standards, and compliance requirements. GenAI is then introduced as a powerful tool to navigate this landscape, streamlining reporting, ensuring adherence to frameworks, and detecting potential greenwashing. The evolution of the GenAI family of models is highlighted alongside real-world use cases, demonstrating its practical impact on sustainability within finance. The importance of human validation and the ethical implications of AI are also addressed. While GenAI offers significant advantages, it also raises important ethical questions. Ensuring the reliability and factual accuracy of AI-generated content is paramount. The chapter discusses the necessity of human validation to mitigate biases and prevent overreliance on AI tools. Maintaining critical thinking and problem-solving skills within the research community is essential to balance the use of AI. Further, the chapter delves into different GenAI models and discusses advanced prompt engineering techniques for unleashing GenAI’s full potential. Finally, it acknowledges the environmental footprint of data centers powering global AI and emphasizes strategies for sustainable AI development. Ultimately, this chapter presents GenAI as an essential tool with great potential to drive a more transparent and sustainable future for the fintech sector.
Keywords: AI, Generative AI, ChatGPT, LLM, fine-tuning, agentic workflow, RAG, prompt engineering, bias, ethical AI, SFDR, guardrails, sovereign AI
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