AI Powered Risk Management: Addressing Cybersecurity Threats in Financial Systems.

The increasing sophistication of cybersecurity threats poses substantial risks to financial systems worldwide, making effective risk management essential. This study explores the integration of Artificial Intelligence (AI) in enhancing cybersecurity risk management within financial institutions. AI-driven tools offer advanced capabilities for identifying, predicting, and mitigating cyber threats, leveraging machine learning algorithms, neural networks, and predictive analytics to detect anomalies and potential breaches in real-time. By automating risk assessment processes, AI systems enhance accuracy in threat detection, reduce response times, and minimize human error, thus strengthening overall cybersecurity resilience. This research highlights key AI-powered techniques such as anomaly detection, behavioral analysis, and predictive threat modeling, which collectively offer financial systems a proactive defense mechanism against cyber-attacks. Furthermore, challenges surrounding AI implementation, including data privacy concerns, regulatory compliance, and ethical considerations, are examined. Through a comprehensive analysis of AI applications in risk management, this paper underscores the transformative role of AI in creating secure, resilient financial ecosystems and presents a framework for financial institutions to adopt AI-driven cybersecurity strategies effectively. Digital innovations hold vast potential to expand financial inclusion, improve efficiency, mitigate risks, and meet customer demands in a dynamic digital economy. However, concerted efforts are needed to address cyber security vulnerabilities, build robust digital infrastructure, up skill workforce capabilities, and design ethical frameworks governing data use. India's digital finance transformation will have far-reaching implications for competitiveness, profitability, and stability of the banking sector. [ABSTRACT FROM AUTHOR]