At the China Development Forum 2026 held from March 22nd to March 23rd, Wu Haisheng, CEO of Qifu Technology, stated in a conversation that Openclaw is a highly capable product, but its power comes at the cost of personal and data security. He emphasized that the more user authorization it receives, the stronger its functionality becomes, making it crucial to find a balance between these aspects.

Wu Haisheng specifically pointed out that applying AI agents in financial scenarios requires extreme caution. Deploying such AI products within an organizational workflow is equivalent to exposing company data on the public internet, significantly increasing data protection risks. For the fintech industry, this risk is even more pronounced. "Because finance involves not just information security but also asset security, leading to a larger risk exposure," he explained.

During the dialogue, Wu further discussed the differences in AI agent application environments between China and other countries. He noted that in foreign markets, platforms for social media and e-commerce generally offer more open API interfaces, allowing AI agents to perform tasks like ordering food or processing payments. In contrast, China's internet has developed along a different path, with practical limitations on interface openness. Consequently, the application of AI agents domestically still requires further exploration.

It is understood that Qifu Technology has already implemented AI technology in various areas, including risk identification, intelligent customer service, and operational decision-making, and continues to explore AI's potential in complex financial scenarios. In 2026, leveraging its AI technological advantages, the company plans to accelerate its expansion into overseas markets, including Europe, Latin America, and Southeast Asia.

Wu Haisheng provided an example: banks face a large volume of information requiring manual processing in their daily operations. For instance, when a company applies for credit, it involves extensive text, image, and video materials. Previously, this relied on human experience, which was not only inefficient but also prone to subjectivity and experiential blind spots.

"When a small or micro-enterprise submits dozens or even a hundred pages of materials, manual processing is prone to errors, carries strong subjectivity, and is highly inefficient," he said. Now, the application of AI has significantly improved processing accuracy and efficiency, "reducing document processing time from one month to just one hour."

Wu believes financial institutions can follow two main paths when applying AI. "First, minimize involvement in tasks related to fund handling. Second, introduce a 'copilot' model where humans remain the final decision-makers." He stated that for the next one to two years, human oversight should still dominate risk control. Only after safety issues are fully validated can a gradual transition to more complex tasks occur. "Tesla has set an example for full automation across all fields: first learn from human drivers, then achieve semi-autonomous driving, and finally progress to FSD (Full Self-Driving)."

Regarding the banking industry's overall attitude towards AI technology, Wu described it as "a mix of excitement and concern." "The excitement comes from breakthroughs brought by technologies like DeepSeek and Openclaw, while the concern is that not adopting them means falling behind, yet using them introduces security risks." He concluded that financial institutions are actively seeking a balance. This process requires both technological iteration and human collaboration, with the technology itself needing greater investment in safety-by-design principles.