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Explaining AI in Finance: Past, Present, Prospects

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  • Barry Quinn

Abstract

This paper explores the journey of AI in finance, with a particular focus on the crucial role and potential of Explainable AI (XAI). We trace AI's evolution from early statistical methods to sophisticated machine learning, highlighting XAI's role in popular financial applications. The paper underscores the superior interpretability of methods like Shapley values compared to traditional linear regression in complex financial scenarios. It emphasizes the necessity of further XAI research, given forthcoming EU regulations. The paper demonstrates, through simulations, that XAI enhances trust in AI systems, fostering more responsible decision-making within finance.

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  • Barry Quinn, 2023. "Explaining AI in Finance: Past, Present, Prospects," Papers 2306.02773, arXiv.org.
    • Handle: RePEc:arx:papers:2306.02773
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    1. Edwards, Lilian & Veale, Michael, 2017. "Slave to the Algorithm? Why a 'right to an explanation' is probably not the remedy you are looking for," LawArXiv 97upg, Center for Open Science.
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