"Harnessing Data Storage Power: Accelerating AI Adoption in the Financial Sector - Highlights from the 2025 Huawei Financial Innovation Data Infrastructure Summit"

[Xiamen, China, March 27, 2025] The 2025 Huawei Financial Innovation Data Infrastructure Summit was successfully held, and the event brought together nearly 400 experts in the field of fintech for in-depth exchanges on the challenges and solutions to the landing of AI in the financial industry.

Actively Exploring AI Landing, Data Attack Becomes Key

China's financial institutions have entered the stage of exploring the application of AI on a large scale. According to Avery Consulting statistics, more than 80% of banking institutions have taken the lead in realizing AI technology landing in areas such as intelligent risk control and precision marketing, and the head institutions have further launched large models of financial pitfalls; at the same time, the securities and insurance industries have also actively introduced AI technology, and scenarios such as quantitative trading and intelligent underwriting have become the focus of technology landing.

However, the efficient development of data assets is still the core bottleneck of AI deep application. First, AI massive data access is difficult, data and model engineering is complex, restricting the efficiency of model development; second, AI infrastructure investment is large, the elasticity of storage and computing resources deployment ability lags behind; in addition, the value of AI data assets surge, the traditional security protection system has been difficult to cope with the risks of ransomware attacks, training data leakage and other risks derived from the AI era.

Proposing Four Storage Innovations to Help the Financial Industry Solve Problems

Zhou Yuefeng, Huawei's vice president and president of the data storage product line, proposed at the conference that “the AI era is the golden age of data, and storage innovation is even more important in the AI era. Data storage can help the financial industry tackle problems in four ways.

Zhou Yuefeng, Vice President and President of Data Storage Product Line, Huawei

AI Data Lake. Huawei's AI data lake solution realizes unified storage of heterogeneous data from multiple sources within the enterprise and breaks the limitations of traditional data centers to achieve global visibility and efficient flow of data, as well as solving the problems of time-consuming data engineering, difficult application docking, and low availability of AI clusters through the AI tool chain ModelEngine.
Storage-computing separation architecture. Decoupling data storage and computing capabilities, financial enterprises can independently expand storage or computing resources according to business needs, enhancing IT investment efficiency. In addition, it also enables centralized management of data assets and promotes cross-cloud and cross-system data sharing.
Storage endogenous security. Through the construction of an efficient data backup system, as well as data anti-ransom capability, it realizes the evolution from passive defense to active protection, and builds a solid line of defense for data assets in the AI era.
All-flash storage media. The high IOPS and low latency of all-flash media can meet the requirements of AI big models for accessing massive data at any time, and at the same time, it can also improve data storage density, save physical space, reduce energy consumption, lower total cost of ownership, and help green low-carbon.
Reaching consensus, the financial industry in action

At the meeting, fintech experts from large state-owned banks, joint-stock commercial banks, and Internet banks shared and exchanged views on hot topics such as storage-computing separation, data security, and all-flash storage. At the same time, Huawei and Cinda Technology Co. Ltd. also jointly released the DCS AI Financial Integration Solution, which aims to improve the quality and efficiency of AI applications in the financial industry, such as intelligent order review, intelligent document processing, and intelligent outbound calling, and accelerate the landing of AI in the financial industry.