In the bustling heart of Shanghai, post the 2025 Spring Festival, a technological transformation began to unfold at the Huatai-PB Wealth Management Building located at 728 Waim Road, Huangpu District. The financial landscape was about to experience a seismic shift, as a leading asset management company unveiled its ambitious integration of advanced artificial intelligence.

The firm, Huitianfu Fund, announced its successful private deployment of the DeepSeek series of open-source models. This strategic move aimed at revolutionizing their core business operations, which encompass investment research, product distribution, risk control compliance, and customer service. The company emphasized that these new models possess enhanced capabilities in language comprehension, logical reasoning, and multi-turn dialogue. Such attributes were expected to not only ensure data security and responsiveness but also tailor optimizations specifically for financial scenarios, ultimately enriching the depth and breadth of financial data analysis and empowering various company functions significantly.

The wave of transformation, however, is not confined to Huitianfu Fund alone. Reports indicate that nearly twenty public funds, including Tianhong Fund, Fortune Fund, Nuon Fund, Guotai Fund, China Universal Fund, Invesco Great Wall Fund, Wanjia Fund, and Bosera Fund, among others, have either completed or are in the process of implementing similar private deployments of the DeepSeek series. This collective leap into the future shows that the finance sector is swiftly adapting to the AI revolution.

Another notable player, Nuon Fund, has also embraced this wave of innovation, completing the local deployment of the DeepSeek financial model while launching its own proprietary "Nuon AI Assistant." This tool is designed based on mainstream AI open-source frameworks and aims to enhance performance in critical business areas such as investment research analysis, customer service, and risk management. As part of their initiative, Nuon Fund is currently exploring intelligent data processing for investment research, dynamic customer tagging analysis, and automation of middle and back-office processes through a series of iterative experimental practices, reflecting a proactive approach to technological adoption.

Tianhong Fund has similarly disclosed its proactive exploration of technologies related to DeepSeek. The company's efforts include rigorous testing of the model's efficacy, training its proprietary large models, and investigating reinforcement learning pathways, with some of these explorations already showing promising results.

The trend of using AI for business applications within asset management has been steadily accelerating since 2021. Many institutions recognized early the potential of AI to assist in product research, analysis, and overall fund operations. A founder of a Beijing-based asset management firm shared insights into their development of a compliance analysis and monitoring model over recent years. This model integrates pre-investment approvals and post-investment monitoring seamlessly into the company’s entire investment process, showcasing a commitment to comprehensive compliance management.

Moreover, this founder elaborated on the rapid pace of information circulation in today’s digital age. In a landscape where information can reach 80% of investors within mere hours, the traditional reliance on researchers and money managers to manually sift through vast amounts of data has become cumbersome. AI tools, on the other hand, offer a significant enhancement in operational efficiency, transforming how investment decisions are made.

A mid-level executive from a public fund in Beijing further articulated the reality of data generation in fund operations. Daily activities yield immense quantities of data across multiple facets, including investments, transactions, securities markets, and client activities. With routine tasks like data entry, report generation, and coding being highly repetitive, the DeepSeek models can automate these operations. This shift leads to reduced manual oversight, improves overall efficiency, and minimizes operational risks.

However, some executives caution that the current stage of private deployments among firms is still in its infancy, making it challenging to quantify the genuine impacts on operations, departments, and personnel. Yet, the consensus is that as organizations engage in further explorations of AI models, the connection to industry data will facilitate knowledge distillation and fine-tuning, ultimately fostering the digital transformation and intelligent upgrades of the fund industry—a transition that may reshape the entire sector.

As for the potential impact on job roles within fund companies, numerous professionals expressed a belief that the growing ubiquity of AI would lead to increased reliance on intelligent customer service solutions, likely diminishing the demand for traditional customer service roles. Instead, there will be a greater need for skilled individuals who can analyze data and enhance customer experiences to elevate the general quality of financial services offered.

Moreover, roles dealing with repetitive tasks are anticipated to reduce gradually, with job functions shifting toward process optimization and systems management. Despite the impending changes fueled by AI advancements, various interviewed professionals conveyed that they are not worried about job losses. Instead, they advocated for a proactive embrace of change and adaptation to the evolving landscape of the financial industry.

In summary, the rise of AI, particularly through the use of specialized models like DeepSeek, is not merely an evolutionary step but a revolutionary leap for the finance sector in China. As institutions like Huitianfu, Nuon, and Tianhong lead the charge, the collaborative and competitive push towards incorporating AI in asset management enhances efficiency and exemplifies a forward-thinking approach poised to redefine the industry's future.