In the third episode of the second season, "MLM & Mantic" delved into the latest advancements and applications of artificial intelligence (AI) in financial systems. The discussion not only covered the latest technologies in the field but also explored how these innovations are reshaping the industry, along with the potential risks and challenges they bring. The program featured several experts in the financial sector who discussed the wide-ranging applications of AI, including risk management, investment decision-making, and customer service. These experts emphasized that through machine learning and big data analytics, financial institutions can achieve more accurate market trend assessments and predictions, enhancing decision-making efficiency and reducing operational costs. For instance, many banks have already implemented AI algorithms to detect fraudulent activities, which has significantly minimized losses. Additionally, the adoption of intelligent customer service systems has become increasingly common, providing 24/7 support and significantly boosting customer satisfaction. Despite its benefits, the integration of AI in the financial sector is not without challenges. One of the primary concerns is data security and privacy protection. Financial institutions handle vast amounts of sensitive information, and ensuring the safety of these data points is a critical issue. Another challenge is regulatory compliance. Current financial regulations often lag behind technological advancements, placing a significant burden on institutions to adhere to outdated rules. Moreover, the transparency and explainability of AI systems remain pressing concerns. The clarity and rationality of decision-making processes are vital for maintaining the trust and credibility of financial institutions. To address these challenges, the experts offered several recommendations. First, they suggested strengthening data security technologies and management practices to prevent data breaches and protect customer information. Second, they recommended proactive engagement with regulatory bodies to advocate for updates and improvements in existing laws. Finally, they emphasized the need to increase the transparency of AI systems, making their decision-making processes more understandable and acceptable to both users and regulators. In summary, the application of AI in financial systems holds great promise, but it must be approached with caution and a commitment to overcoming various challenges. Ensuring the healthy and secure development of these technologies is essential for their long-term success and positive impact on the financial industry.