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The swift progression and widespread integration of Artificial Intelligence (AI) across numerous fields has been causing major shifts in conventional paradigms.One of the prime examples of such transformation is evident in the finance sector.This document delves into the immediate implications, future opportunities, the challenges being faced and the future outlook of AI in finance by conducting an exhaustive review of academic papers, industrial studies, and real-world case studies.Our research indicates that AI's impact on areas like risk management, trading, customer assistance, fraud detection, and personalization of financial services has been notably significant, boosting efficiency, security, and customer contentment.However, we also discuss the critical hurdles that arise with the implementation of AI, such as ethical concerns about data privacy and biases, the mystery surrounding AI's 'black box' problem, and the potential job losses due to automation.Our paper concludes that although AI has the potential to bring about significant changes in the finance industry, it is crucial to overcome the associated ethical, trust, and regulatory challenges to maximize its benefits.Future investigations should focus on creating ethically considerate, transparent, and robust AI tools that are compliant with and can excel in the regulatory landscape of the finance industry.
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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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