Generative AI and Its Role in Shaping the Future of Risk Management in the Banking Industry

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@article{1704257,
      author = {Suprit Kumar Pattanayak},
      title = {Generative AI and Its Role in Shaping the Future of Risk Management in the Banking Industry},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {6},
      number = {10},
      pages = {1012-1024},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1704257.pdf},
      abstract = {This study investigates the transformative impact of Generative Artificial Intelligence (GAI) on risk management practices within the banking sector. As financial institutions grapple with increasingly complex risk landscapes, GAI emerges as a powerful tool for enhancing predictive capabilities and decision-making processes. Through a mixed-methods approach, incorporating quantitative analysis of 500 global banks and qualitative insights from 50 senior risk management executives, this research explores the current state of GAI adoption, its potential applications, and the challenges in its implementation.
Our findings reveal that early adopters of GAI in risk management have experienced a 37% improvement in fraud detection rates and a 28% reduction in false positives in credit risk assessments. Moreover, GAI-driven scenario generation has enhanced stress testing processes, allowing banks to model a 215% broader range of potential economic scenarios compared to traditional methods. The study also uncovers that GAI applications in natural language processing have improved the efficiency of regulatory compliance processes by 42%, significantly reducing the time and resources required for document review and reporting.
However, the research also identifies significant challenges, including data privacy concerns, the need for explainable AI models to meet regulatory requirements, and the skills gap in AI expertise within traditional banking structures. A notable finding is the disparity in GAI adoption rates, with large multinational banks investing heavily in these technologies, while smaller regional banks lag, potentially exacerbating competitive imbalances in the industry.
The study concludes that while GAI holds immense potential for revolutionizing risk management in banking, its successful integration requires a holistic approach encompassing technological infrastructure, regulatory alignment, ethical considerations, and workforce upskilling. These findings have profound implications for banking strategies, regulatory frameworks, and the future landscape of financial risk management.},
      keywords = {Generative Artificial Intelligence (GAI), Risk Management, Banking Industry, Machine Learning, Predictive Analytics, Fraud Detection, Credit Risk Assessment, Regulatory Compliance, Stress Testing, Financial Technology (FinTech), Ethical AI, Data Privacy, Model Explainability, Digital Transformation, Financial Stability},
      month = {April},
  }