Transforming Capital Adequacy Assessment: The Role of Artificial Intelligence in Comprehensive Capital Analysis and Review
DOI:
https://doi.org/10.22399/ijcesen.4266Keywords:
Artificial Intelligence, Capital Adequacy Assessment, Machine Learning Models, Regulatory Compliance Automation, Risk Data Aggregation, Stress Testing FrameworkAbstract
The extensive capital review and analysis process is an integral regulatory framework guaranteeing financial institutions are adequately capitalized with buffers during times of economic duress. Conventional practices in annual stress testing exercises are strongly based on manual data consolidation, static econometric model formats, and time-consuming documentation practices, taking up significant institutional resources while opening up scope for errors and inconsistencies. The advent of artificial intelligence technologies offers revolutionary possibilities to reengineer capital adequacy evaluation processes on several fronts. Machine learning techniques provide for reconciling data automatically and assuring quality, compressing preparation schedules while increasing data accuracy. Generative artificial intelligence architectures allow for the design of elaborate stress scenarios beyond the usual regulatory boundaries, incorporating intricate macroeconomic interactions and institution-specific weaknesses. Sophisticated predictive models using gradient boosting and neural network topologies exhibit better forecasting precision for credit losses and revenues in stressed scenarios. Natural language processing tools expedite the generation of technical reports and regulatory narratives, whereas robotic process automation provides consistent populating of templates and intelligent validation. Distributed ledger technologies integrated with capabilities to continuously monitor turn episodic compliance exercises into real-time resilience frameworks, enabling real-time management of capital. The effective incorporation of artificial intelligence in regulatory stress testing calls for vigilant consideration of model transparency, explainability requirements, and governance rules that guarantee supervisory acceptability while upholding the quintessential goals of financial solidity and stakeholder safeguarding in times of economic turmoil.
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