Ethical AI in financial decision-making: Transparency, bias, and regulation

Abstract

Artificial Intelligence (AI) is progressively reshaping the legal and regulatory landscape by enhancing the ability to interpret legal texts and automate compliance processes. This paper proposes a conceptual AI model tailored to the nuanced domain of legal text interpretation and regulatory compliance. We analyze the technical requirements, current challenges, and the proposed architecture's alignment with legal reasoning and ethical principles. By integrating Natural Language Processing (NLP), Machine Learning (ML), and rule-based reasoning, the proposed framework addresses semantic ambiguity, multi-jurisdictional complexities, and legal language variability. The research also evaluates potential implementations in corporate legal departments and regulatory agencies to promote transparency and efficiency.