The technology and financial sectors are currently captivated by the term "raising lobsters." This is not a reference to aquaculture but a colloquial nickname for the open-source AI agent, OpenClaw. The emergence of this "digital employee," capable of autonomously operating computers and executing tasks, signals that artificial intelligence is progressing from simple conversational interactions to a new phase of deep integration into business processes. However, this technological surge is accompanied by undercurrents of risk. Recent warnings issued by the Ministry of Industry and Information Technology highlight that some OpenClaw instances, under default or improper configurations, pose significant security risks, making them highly susceptible to cyber attacks and information leaks. This serves as a crucial alert for AI applications across society, particularly within the financial industry.

For the financial sector, where every second counts and data is dense, the operational capabilities represented by OpenClaw undeniably showcase vast application potential. A single instruction can trigger automated retrieval of financial information, collection of trading data, and generation of research reports and charts. It can perform tasks like announcement extraction, data cleansing, email distribution, and market monitoring 24/7. By directly connecting to databases and business terminals, it frees professionals from repetitive labor. This "end-to-end" automation is viewed as an effective tool for boosting efficiency and reducing costs.

Indeed, China's financial industry has already taken substantial steps in intelligent application. For instance, in October 2025, Industrial and Commercial Bank of China leveraged large models and AI technology to develop an AI Trader for bond trading, reshaping trading models to handle massive daily inquiries and high-concurrency transactions, thereby enhancing effectiveness and scalability through digital tools. In September 2025, Ping An of China noted during its interim results presentation that Ping An Property & Casualty had developed four core capabilities: understanding customer graphic and text information, automating auto insurance quotes, dynamically adjusting plans, and intelligent Q&A. It overcame challenges in automatically recognizing and understanding a large volume of unstructured, non-standard documents like new vehicle certificates and customs forms. In scenarios involving intelligent auto insurance policy issuance through agent channels, over 86% of policies were issued automatically by AI. These cases demonstrate that empowering finance with AI to serve the real economy is a vital pathway to high-quality development.

However, technological application must advance hand-in-hand with risk management. The financial industry's lifeline is stability, compliance, and risk control. Facing intelligent agents like OpenClaw, which possess characteristics such as autonomous decision-making, continuous operation, and the ability to call upon systems and external resources, the potential risks cannot be underestimated. The issue of "blurred trust boundaries" mentioned in the MIIT warning is particularly acute in finance. If AI agents are deployed without strict permission controls, robust audit mechanisms, and security hardening, they could be induced by malicious prompts, suffer from configuration flaws, or be maliciously taken over, leading to unauthorized operations. This could transform an efficient "digital employee" into a dangerous "digital insider threat."

Specifically, the risks are concentrated in three dimensions. First, regarding data security, agents require high-level permissions for file access, browser control, and API interfaces to complete tasks. If subjected to "prompt injection" attacks or hijacked by malware, they could massively steal core data like customer information and transaction records, causing severe damage to institutional reputation and client rights. Second, in terms of compliance and accountability, financial AI applications must adhere to regulatory red lines requiring explainable algorithms, traceable decision-making processes, and accountable risk responsibility. If AI-generated conclusions or triggered transactions are biased, misleading, or non-compliant, it could provoke unforeseeable chain reactions. Third, concerning system protection, if numerous instances have open ports by default and lack effective authentication, they become directly exposed to public internet risks. Attackers could even infiltrate business systems as "legitimate digital avatars" to carry out disruptive activities more covert than traditional cyber attacks.

Therefore, amidst this "lobster-raising" tech frenzy, the financial industry must maintain冷静 (calmness) and prudence. It is crucial not to overlook necessary risk assessments, permission segregation, and security audits due to blind trend-following or a rush to "try the new."

Trust is the foundation of finance, and compliance is the bottom line for technology application. OpenClaw has ushered in a new era of AI execution, an irreversible technological trend. The efficiency gains, process optimization, and labor savings it brings are aspects the financial industry should actively embrace, study deeply, and utilize effectively. However, high-quality development in finance has never been about being the fastest, but about ensuring the steadiest progress. In the heat of the "lobster-raising" trend, the financial sector should maintain strategic clarity and a cautious approach, strengthening risk analysis, fortifying protective barriers, and strictly guarding compliance checkpoints. It should incorporate more冷静 (calm), more layers of protection, and additional reviews into the innovation wave, promoting stable and enduring fintech advancement through security and orderly compliance. The goal is to ensure AI remains a "capable assistant" for decision-making, not a "technological master" beyond control. By upholding integrity in innovation and prioritizing safety, technological empowerment should consistently serve high-quality business development, never overriding the fundamental底线 (bottom line) of financial security. This is the correct stance and operational logic China's financial industry should adopt as it embraces AI development.