Analysis of Core Difficulties in the Wealth Management Transformation of Securities Firms
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Based on the latest industry research reports and market analysis, I have systematically sorted out the main difficulties and challenges faced by securities firms in their wealth management transformation:
- According to KPMG’s 2025 China Securities Industry Survey Report, the fund sub-custody commission income of securities firms in 2024 was 11 billion yuan, a 35% decrease from 2023, accounting for only 51% of that in 2021 [1]. The public fund fee reduction reform has further intensified competition in sales channels, and the securities firm industry is facing reshaping.
- Under the “one participation, one control, one license” policy, no application for public fund licenses from securities firm asset management subsidiaries was approved throughout 2024 [1]. The transformation of large aggregation products to public funds is nearing completion. If the public fund license is still not obtained upon expiration, management will face the difficult choice of liquidating the product or changing the manager.
- The CSRC’s Action Plan for Promoting the High-Quality Development of Public Funds has for the first time proposed a detailed classification evaluation mechanism for sales agencies, incorporating indicators such as the scale and proportion of equity fund holdings, investor profit and loss, and holding periods into the evaluation index system [1], putting forward higher compliance requirements for the wealth management business of securities firms.
- The traditional seller’s model of securities firms, which is oriented towards “product sales”, is deeply rooted. The transformation to the buyer’s advisory model centered on “customer interests” requires full-system changes covering strategy, products, services, and investment research [2]. The original commission-based incentive assessment model is difficult to change quickly.
- Under the buyer’s advisory model, it is necessary to establish an assessment system centered on customer returns and service satisfaction, fundamentally achieving deep alignment with customer interests [2]. This requires securities firms to reconstruct their internal incentive mechanisms, which may affect revenue in the short term.
- The implementation of regulatory provisions has affected the scale and structure of commission income in the short term [1]. Before the new profit model matures, securities firms are facing short-term pains.
- The industrialized cultivation of investment advisory capabilities is one of the biggest current pain points. Excellent investment advisors are scarce resources, and AI should serve as a “capability amplifier” [3]. Multiple securities firms are recruiting heads of fund advisory business with annual salaries of millions, but competition for talents is fierce.
- The ability to convert research resources into wealth management business is insufficient, and frontline investment advisors lack effective investment research support. Although Zhongtai Securities has actively explored the conversion of research institute resources to wealth management, the overall conversion efficiency of the industry needs to be improved.
- This is a key yet most easily overlooked link in trust-building, and a mature mechanism for emotional management during market fluctuations has not yet been formed [3].
- Against the industry backdrop of cost reduction and efficiency improvement, how to cope with the pressure of digital transformation and technology investment has become a key issue to be resolved urgently [1]. Fintech transformation requires substantial financial support, but it is difficult to generate obvious returns in the short term.
- The traditional core operation system architecture is rigid, with no scalability or extensibility, and marginal costs rise rapidly with the increase in business volume [4]. Old systems are difficult to support the needs of new-type wealth management businesses.
- IT professionals proficient in traditional languages such as COBOL are increasingly scarce, and system upgrades and transformations face talent bottlenecks.
- The customer structure of securities firms is dominated by retail investors, and the service capabilities for high-net-worth clients and institutional clients are relatively weak. Leading banks occupy the high-net-worth market through digitalization, putting competitive pressure on securities firms.
- Customer needs are becoming increasingly personalized, but service models are still biased towards standardization, making it difficult to meet the full-life-cycle wealth management needs of customers with different risk preferences.
- The buyer’s advisory model requires long-term accompaniment and services to establish customer trust, and it is difficult to form scale effects in the short term.
- Banks, funds, and third-party wealth management institutions are actively entering the wealth management market. Commercial banks have formed competitive pressure on securities firms by virtue of their customer resource endowments and comprehensive financial synergy advantages [3].
- The advantages of securities firms with complete layouts of the three licenses under the “one participation, one control, one license” policy have gradually emerged. Resources are concentrated among leading firms, and small and medium-sized securities firms are facing greater survival pressure.
- Under the pattern of open product shelves, how to build a core moat has become a difficult problem, and securities firms need to identify their own positioning to form differentiated competitive advantages.
- The wealth management transformation requires interdisciplinary talents who understand both finance and technology, as well as both investment research and customer service, and such talents are extremely scarce.
- Traditional salary systems are difficult to attract and retain excellent talents, especially in emerging fields such as robo-advisory and quantitative investment.
- The training system for investment advisors is still imperfect, making it difficult to support the construction of large-scale professional investment advisor teams.
The wealth management transformation of securities firms is a systematic project involving in-depth changes in multiple dimensions such as regulatory compliance, business models, technological capabilities, and talent teams. Facing the above difficulties, the industry needs to adhere to the concept of “investor-centric”, and enhance core competitiveness by improving research capabilities, accelerating technology empowerment, and creating new models of diversified development [1]. The buyer’s advisory model, with its core logic of “customer interests first”, has become an inevitable direction for industry transformation [2]. In this process, securities firms that can take the lead in breaking through the above difficulties will gain an advantageous position in the new round of competition.
[1] KPMG. 2025 China Securities Industry Survey Report. August 2025. (https://assets.kpmg.com/content/dam/kpmg/cn/pdf/zh/2025/08/mainland-china-securities-survey-2025.pdf)
[2] 21st Century Business Herald. Embracing the Transformation of Buyer’s Advisory Business, Securities Firms Intensively Launch New Wealth Management Brands. December 16, 2025. (https://www.21jingji.com/article/20251216/herald/aad16b8f1b0b1bc814d7a43fb67a2121.html)
[3] Zeng Gang (Shanghai Finance and Development Laboratory). Restructuring of Bank Wealth Management Architecture to Seize 300 Trillion Yuan of Resident Assets. Eastmoney.com. January 15, 2026. (https://wap.eastmoney.com/a/202601153620807035.html)
[4] EY. Technology Drivers of Post-Trade Operations: Landscape Analysis and Solutions. (https://www.ey.com/content/dam/ey-unified-site/ey-com/zh-cn/insights/strategy/documents/ey-technology-drivers-of-the-post-trade-operations-report-zh.pdf)
Insights are generated using AI models and historical data for informational purposes only. They do not constitute investment advice or recommendations. Past performance is not indicative of future results.
About us: Ginlix AI is the AI Investment Copilot powered by real data, bridging advanced AI with professional financial databases to provide verifiable, truth-based answers. Please use the chat box below to ask any financial question.