From Fintech to Green Fintech: How to Decarbonize the AI in the Financial Domain

Abstract

Machine Learning and Deep Learning are spreading at incredible pace in finance. However, the related energy consumption lacks in coherence with the sustainability requirements of banks and financial institutions. Particularly, as the energy required to run complex algorithms increases, more CO2 is released because of the power grid relying mostly on fossil fuels. While techniques are arising to mitigate the carbon footprint of AI, Fintech is facing the challenge of integrating such strategies within the peculiarities of the domain, which requires timeliness, data protection and compliance. In this work, we present the state-of-the-art Green AI techniques, reporting the available experimental results, and critically evaluating their applicability in the financial domain. This contribution is useful for financial institutions, Fintech startups and regulatory bodies who wants to measure and mitigate the impact of AI in the field, decarbonize old or new AI-based products and services, and assess the effectiveness of decarbonization efforts.