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Green Finance Risk Prediction

  • Unique Paper ID: 176334
  • Volume: 11
  • Issue: 11
  • PageNo: 5032-5035
  • Abstract:
  • Sustainability has become a focal point of importance for organizations aiming to comply with changing regulatory requirements and societal pressures. This article introduces a new framework that combines the strengths of supervised machine learning and generative AI to help tackle important sustainability issues. The solution suggested in this paper automatically identifies potential environmental and governance risks by processing organizational, geographic, and industrial data. By converting unprocessed ESG (Environmental, Social, and Governance) information into usable information, the system facilitates precise and effective sustainability analyses. Apart from predictive risk modeling, the system also uses generative AI to generate compliance-ready sustainability reports based on international standards. This reduces human effort, mistakes, and regulatory compliance delays. The use of AI technologies in business processes enhances decision-making, facilitates sustainable development goals, and decreases reputational and financial risk. It facilitates the path to data-driven, future-oriented ESG strategies that empower organizations to drive transparency, accountability, and long-term value. Its increased application contributes towards building a global sustainability culture by offering a scalable, smart tool that can adapt to varying stakeholder needs.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 11
  • PageNo: 5032-5035

Green Finance Risk Prediction

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Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

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