Financial crisis is a serious threat to economic stability, so an effective early warning system is needed to detect and anticipate potential risks early on. The implementation of artificial intelligence (AI) in financial crisis early warning systems offers significant advantages through big data analysis capabilities, non-linear pattern detection, and more accurate and faster risk prediction than conventional methods. Studies have shown that machine learning and deep learning algorithms can improve crisis prediction accuracy, expand the scope of risk monitoring, and support more responsive decision-making by regulators and financial industry players. However, challenges such as data quality, security, model transparency, and human resource readiness still need to be addressed for optimal AI implementation. This study concludes that with good governance, investment in infrastructure and human resources, and adaptive regulations, AI can be a strategic tool in strengthening early warning systems and maintaining financial sector resilience in the digital era.
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