AI-Driven Financial Risk Monitoring and Adaptive Decision Support for Cloud-Based Banking Platforms

  • Authors

    • Vishwaram Software Engineer, USA. Author

    DOI:

    https://doi.org/10.67228/3142788X/IJMLPA-V9I3P101

    Published 07-04-2026

  • Artificial Intelligence, Financial Risk Monitoring, Cloud Banking, Machine Learning, Adaptive Decision Support, Explainable AI, Operational Resilience, Financial Data Governance

    Issue

    Vol. 9 No. 3 (2026)

    Section

    Articles

  • Abstract

    The growing use of cloud computing and artificial intelligence (AI) in banking is introducing a new set of risks to banks’ financial, operational, cyber security and liquidity profiles. Many traditional risk management systems use pre-defined rules and fragmented data, which limits their capacity to detect emerging risks. This study presents a conceptual model for an AI-enabled financial risk monitoring system and adaptive decision-making process within cloud-based banking environments. The model combines cloud native data management, machine learning, explainable AI, risk assessment prioriti- zation, and policy aware decision support to increase risk visibility, transparency and operational resiliency. A literature review was conducted to evaluate existing models and identify research gaps. In addition to being able to continuously monitor risk, the model emphasizes the necessity of high quality data, model governance and human oversight. Since the model has not been empirically tested, it will require empirical validation before its usefulness can be proven.

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