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In the evolving landscape of financial services, Artificial Intelligence (AI) has emerged as a transformative force, driving innovation and efficiency. However, its integration within the sector is accompanied by significant legal and regulatory challenges, necessitating a nuanced understanding of compliance frameworks. This paper delves into the intricate relationship between AI applications in finance and the regulatory environment governing them. We explore the current regulatory landscape, identifying key areas of concern such as data privacy, ethical use of AI, transparency, and accountability. Through a comprehensive literature survey, we highlight the evolving nature of regulatory guidelines across different jurisdictions and the implications for stakeholders in the financial ecosystem. Our proposed work introduces a novel framework designed to assist financial institutions in navigating these complexities, ensuring that AI applications are developed and deployed in a manner that is compliant with existing and foreseeable regulatory requirements. The framework is underpinned by algorithms that facilitate compliance checks and risk assessments, incorporating mathematical models to predict regulatory alignment and potential breaches. We present the implementation of our framework through a series of case studies, demonstrating its effectiveness in enhancing compliance processes. Results are analyzed using graphs and tables to illustrate the impact of our approach on regulatory adherence. The conclusion underscores the importance of proactive regulatory engagement and the adoption of sophisticated compliance tools in harnessing the full potential of AI in finance.
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Stored only when both papers are in the corpus — 23 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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