Guolian Minsheng Securities: Combining Finance and AI is the Main Development Trend for the Future, Suggests Paying Attention to Financial Enterprises that Have Already Established a Presence in the AI Field.

Guolian Minsheng Securities released a research report stating that on January 12, 2026, the daily trading volume of A-shares hit a historical record, reaching the milestone of 3.6 trillion yuan for the first time, surpassing the previous historical peak of 3.49 trillion yuan. The proportion of financial institutions investing in AI is increasing, and related companies are expected to benefit. There is a vast market for AI+Finance in both the ToB and ToC sectors. It will take time to establish a stable payment model, but with improved actual effects, the consumer side may experience rapid growth after gaining customer recognition. The combination of finance and AI is the main development trend for the industry's future, and it is recommended to pay attention to financial enterprises that have already laid out their strategy in the AI field. The main points of view of Guolian Minsheng Securities are as follows: The hot market trading combined with the support of the "15th Five-Year Plan" policies are driving the development of financial AI. The record-breaking daily trading volume of A-shares has pushed the stock trading industry further due to the recent record market trading volume, further promoting the development of stock trading software, brokerage trading platforms, and data analysis markets within the financial AI sector. Li Wei, the director of the Science and Technology Department of the People's Bank of China, stated during the China Wealth Management Forum that in the "15th Five-Year Plan" period, continuous planning leadership will be essential to formulate a new stage of financial technology development planning, with a focus on deepening the application of artificial intelligence as a key core content for the "15th Five-Year Plan" financial technology development. AI+Finance may become a future trend. The integration of finance and AI has demonstrated success in certain scenarios, and the continuous expansion of these scenarios may lead to market expansion. Driven by advancements in model technology, AI+Finance is reshaping the traditional financial work model. Many scenarios have achieved efficiency improvements by replacing human labor with large models. Under the demonstrated success of certain AI scenarios, the financial sector may experience further applications of AI in the future, leading to an expansion of market size. Some roughly categorized AI-ized scenarios include: 1) Data processing and visualization: Financial analysis: Automatically compare budget against actual performance, identifying key reasons for changes in profit and loss statements. Banking and credit approval: Quickly process financial statements of borrowing companies, using AI to quickly detect cash flow abnormalities or negative income trends. Investment research: Upload financial statement data of listed companies and use AI for fast historical trend analysis and cross-referencing of key financial indicators. 2) Event analysis: Automated due diligence (DD): Quickly scan the global news database of target companies, regulatory filings from the past 10 years, and upstream and downstream supply chain risks. Real-time sentiment and narrative monitoring: Utilize advanced NLP algorithms to monitor global media sentiment changes for specific assets, tracking alpha profit opportunities. 3) Financial processing: Invoice management: Turn messy Excel invoices into an automated workflow with clear progress tracking. Automated reconciliation: Automatically match bank statements, ERP systems, and Excel differences, saving time on manual reconciliation. According to McKinsey data forecasts, generative AI could bring an additional value of $200 billion to $340 billion to the banking industry. If AI's full potential is realized, it could bring about a potential profit increase of 14%-24%. The proportion of financial institutions investing in AI is increasing, and related companies are expected to benefit. According to data from Sina Finance, 72% of financial institutions invested in generative AI in 2025, which is double the proportion in 2024. The increasing investment proportion of financial institutions in AI may lead to an overall market size growth. There are differences between the ToB and ToC sectors, and besides industry beta, financial companies embracing AI may gradually establish an alpha advantage. There is a vast market for AI+Finance in both the ToB and ToC sectors. The ToB market is expected to grow ahead of the ToC market, with high AI adoption rates and multiple scenario implementations. The B-side's large clients include banks, brokerages, insurance companies, which have a high AI acceptance rate and sufficient funds for growth maintenance. The C-side applications mainly include banking apps, AI question and answer assistants, analytical agents and conversational assistants on stock trading software, and premium VIP versions. It will take time to establish a stable payment model, but with improved actual effects, the C-side may experience rapid growth after gaining customer recognition. Some financial companies embracing AI are gradually gaining advantages in actual business operations. For example, Hithink RoyalFlush Information Network proposed the "Allin AI" strategy in 2019, achieved large model implementation in 2024, and commercial implementation in 2025, covering intelligent investment advisory, investment research decision-making, virtual sign language translation (with a patent), and agent development. According to data from Analysys Qianfan, in September 2025, Hithink RoyalFlush Information Network ranked first in the industry with 37.21 million monthly active users, maintaining a year-on-year growth of 8.78%, with a user base approximately double that of the second-ranking company. Some companies embracing AI may have gradually established an alpha advantage. Risk warning: Financial policy risks, unexpected IT spending for large financial institutions risks.