The advent of DeepSeek has significantly increased the possibility of democratizing artificial intelligence (AI), prompting numerous brokerage firms to extend their applications of AI within investment advisory servicesAs reported by various brokerages interviewed by Securities Times reporters, AI is currently seeing scaled applications primarily in scenarios characterized by high tolerance for errors and relatively simple tasksWhile AI’s application has become quite prevalent in areas such as content generation and product research, it still lacks the required trust in more complex business scenarios like investment portfolio management.

There’s no denying that AI has dramatically diminished the competitive advantages that brokerages held in these sectorsThis change indicates that companies proficient in this technology can potentially rival brokerages in specific business situationsIn this context, the question arises: how can brokerages build a 'moat' around their investment advisory services? The potential answers could involve offering personalized services, providing exclusive data, and ensuring comprehensive collaboration—assets that brokerages might not want to overlook.

Enhancing Multi-Business Scenarios

The recent strides in general-purpose AI technology, as represented by platforms like DeepSeek, are having a far-reaching impact on investment advisory services and many other sectors, pushing the boundaries and potential of smart advisory progress even furtherA representative from Ping An Securities, for instance, mentioned that "in the short term, the scaled application of AI primarily occurs in scenarios with higher tolerance for error and simpler tasks." Such scenarios have greater specification for reproducibility, and the accuracy demands for model outputs are relatively lowerAI can thereby facilitate automation and process management through powerful models, leading to significant cost savings and efficiency gains

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Even minor deviations are unlikely to have a noticeable impact on users.

From this perspective, AI is likely to be prioritized in investment advisory content creation and product research domainsIn the content generation phase of advisory services, AI can rapidly produce fundamental content like market analysis reports and interpretations of investment strategies, significantly enhancing output efficiencyAccording to a representative from Huafu Securities, "We have learned from many industry peers that AI can generate a basic market analysis report in just a minute; further instructions can be used to revise and polish it, resulting in a publishable article within about ten minutesIn contrast, manual drafting typically requires around 2.5 hoursImportantly, AI can also promptly update content based on real-time market dynamics, ensuring its timeliness and accuracy, allowing advisors to devote more time and energy to valuable in-depth analysis and customer communication."

Additionally, AI exhibits promise in areas such as product research and portfolio risk managementThe same Huafu Securities representative explained that AI can sift through mountains of financial product information efficiently, analyzing historical performance, risk features, and providing comprehensive data support to advisory professionals, thereby enabling faster and more precise identification of suitable productsWith respect to portfolio risk management, AI can monitor risk indicators in real-time, employing advanced algorithmic models to assess how market changes might affect portfolios, issuing timely warnings, along with risk mitigation strategies and recommendations.

However, the representative from Ping An Securities cautioned that in investment portfolio management and risk control processes, there exists a high level of specialized knowledge and complex decision-making requirementsThis necessitates a deep understanding of niche knowledge areas and procedures, as the accuracy and reliability of outcomes from AI models hold critical importance

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Any errors in this domain could lead to significant repercussions and losses, thus demanding a cautious application approach.

Local Deployment of AI

With constant updates and iterations of domestic AI large models, many brokerages are proactively embracing the wave of technological advancement and beginning to reap the benefits it bringsGuotai Junan has conveyed that since 2023, the company has been gradually exploring the potential of AI large models in the securities investment advisory landscape, collaborating with partners to build a large model specializing in securities involving hundreds of billions in parameters—the Junhong Lingxi modelThis model aims to offer investors personalized, smart, and high-quality investment services.

As soon as the DeepSeek-R1 model was released and made open source, Guotai Junan expedited a privatization deployment, applying explorations in areas such as investor education and credit servicesDuring the Spring Festival this year, China CITIC Bank completed its localized deployment of DeepSeek, making strides in areas like intelligent Q&A, decision-support assistance, AI advisory assistants, and strategy optimization within advisory service scenariosThese advancements are fostering better efficiencies for professional advisors in terms of material collection, trend tracking, and preliminary drafting.

In the realm of wealth management, Guojin Securities has extensively utilized intelligent tools to boost service efficiency while offering more precise investment recommendations and personalized user experiencesTools such as the "Shadow Account," tailored for account optimization, and "Wave Master," a timing tool based on massive market data analysis, exemplify this push to enhance customer experienceFurthermore, Guojin Securities plans to implement DeepSeek into internal operational scenarios, augmenting everyday tasks in advisory, research, compliance, and building knowledge bases for large model Q&A, thereby powering their business growth.

Strengthening Business Moats

Amidst the expanding applications of AI, third-party platforms providing investment advice appear to "understand" their users better

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This scenario incites brokerages to continuously introspect—what, indeed, constitutes the 'moat' of investment advisory services?

The competitive edge, according to a representative from Ping An Securities’ brokerage business department, stems not solely from algorithms but from leveraging specialized knowledge within the financial realm to transform cold hard data into warm value creationThe moats can be summarized as: one being professionalism and the other focusing on value creation at the application levelDongguan Securities elaborated on its understanding of the core competitive advantage of investment advisory services by emphasizing facets such as professional capabilities, resource support, data aspects, client trust, and comprehensive service offerings.

They argue that outstanding brokerage advisory teams bring a wealth of financial knowledge and market experience, allowing them to provide more comprehensive advice and asset allocation strategies that truly resonate with their clienteleMoreover, brokerages possess internal customer data that far outweighs what third-party platforms offerWhen the synergy of the broker’s advisory team combines with an in-house AI platform, the overall efficacy is substantially higher than that of third-party servicesTrust and support foster long-standing relationships between advisors and clients, allowing them to provide not just investment insights but emotional backing to maintain rational investment decisions during market fluctuationsFurthermore, brokerages typically offer a broad array of services, including advisory, asset allocation, and margin financing, thereby better addressing clients’ investing and funding needs.

Guotai Junan's representatives noted that as AI technologies evolve, the core competitiveness of brokerage advisory services is progressively shifting from a model centered on human expertise and informational advantages to a hybrid approach incorporating “data sovereignty, complex scene service, AI collaboration, and an open ecosystem.”

In more specific terms, the unique data advantage brokerages hold includes deep business data, user behavior metrics, and client-related information that uniquely positions them to understand their investors

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