Wang Feng, Vice President of Tencent Cloud: Financial institutions are accelerating the value of data elements

China-Singapore Jingwei, October 20 (Wei Wei, Lin Wansi) In recent years, data, as an important factor of production, has attracted more and more attention from financial institutions. By deeply mining the value of data, financial institutions can greatly improve their capabilities in risk control, accurate decision-making, and financial innovation, and achieve high-quality development.

At present, what are the blockages in the application of data elements in financial institutions? How to do a good job in data element management? How to view the role of large model technology in the flow of data elements? On the 19th, Sino-Singapore Jingwei had a conversation with Wang Feng, Vice President of Tencent Cloud, during the 2024 Financial Street Forum Annual Meeting, and the following is a transcript of the interview (slightly deleted):

Wang Feng, Vice President of Tencent Cloud. Photo courtesy of the interviewee

China-Singapore Jingwei: What are the difficulties and blockages in the application of data elements in financial institutions?

Wang Feng: First of all, the core of data elements is data, and financial data has the characteristics of high value, high density and high quality. Therefore, the most important thing for financial institutions is to ensure the "security" of data. In the past, in order to protect and process this data, financial institutions actually used relatively expensive and redundant architecture systems to store and use this data, such as IBM mainframes and Oracle centralized databases, which had poor scalability and high expansion costs. How to achieve a balance between high safety, high efficiency and low cost has become a difficult point.

Second, in the past, the system structure of financial institutions determined that many of its data were scattered and siloed, because the systems of financial institutions were gradually established. At present, a large number of businesses need to process massive amounts of data, and the cost of technology should be reduced when using these data, otherwise the cost of storing massive amounts of data with expensive systems will become unbearable, which will lead to insufficient processing and analysis capabilities and affect the efficiency of data value mining.

More and more financial institutions are now aware of the importance of data elements and are reimagining their data infrastructure. When Tencent cooperates with financial institutions, most of its applications are based on Internet technology to process massive amounts of data, such as proprietary cloud TCE, big data platform TBDS, distributed database TDSQL, etc., which can not only meet the requirements of finance for data security, but also break the past information silos, and the cost of processing data is affordable. Only when the data infrastructure is in place can the data elements be truly utilized.

China-Singapore Jingwei: For financial institutions, how should they do a good job in the management of data elements?

Wang Feng: First, to improve the ability to collect and store data, financial institutions should establish a massive data collection process and technology platform. The second is to improve data governance capabilities, carry out hierarchical management of data, and build a data security evaluation system. The third is to improve data operation capabilities, to achieve a balance between cost and quantity of data, and to use these data in business.

China-Singapore Jingwei: How does Tencent Cloud work with financial institutions to jointly explore the business value of data elements?

Wang Feng: Tencent Cloud's first concern is how to provide a cost-balanced and secure technical architecture to collect data, and work with financial institutions to explore the business value of data elements. This cooperation includes the joint development of new technologies and applications, as well as the efficient use of data while ensuring data security through the deployment of databases, big data platforms, privacy-preserving computing, security, blockchain, and other technologies.

Specifically, in the supply stage of data elements: through big data technology, massive data from different sources can be efficiently integrated and governed, ensuring the quality and consistency of data, and providing a solid foundation for subsequent data circulation and application.

In the circulation stage of data elements: blockchain and privacy computing technology are used to ensure the identity and traceability of data in the process of circulation and use, and ensure its security, so as to protect personal privacy and data security.

In the application stage of data elements: Artificial intelligence technology is used to conduct in-depth analysis and mining of data from more sources under the premise of security and compliance, provide intelligent decision support, and help financial institutions optimize business processes, improve service experience, and improve risk management capabilities.

Tencent Cloud also cooperates with application developers in the financial industry to explore new application processes and operations, improve the IT resilience and big data processing capabilities of the entire industry, and provide technical data systems, while greatly reducing industry costs and expanding data storage capacity to terabytes, which can generate a lot of new business value after processing.

Nowadays, with the application of AI large model technology, the business and service models of the entire financial industry will change. In the past, banks had to handle customer business through a large number of counters. Now, many businesses can be handled remotely, through real-time audio and video technology to connect the remote people, through the digital person to provide an image, the background is actually the staff to connect to the video, so that customers can handle complex financial business. This can help banks save business costs and broaden the service boundaries, for example, people in remote mountainous areas can enjoy the same financial services.

Zhongxin Jingwei: How do you view the role of large model technology in the value mining of data elements?

Wang Feng: The large model must first have enough data to train, and to make a large financial model, it must have massive financial data. After receiving training on a large amount of data, the large model can help financial institutions improve their financial risk control capabilities, realize customer service automation, personalized recommendation of financial products, etc. Large model technology is also conducive to the innovation of financial products. There are many financial products that are calculated by data models, and the optimization of risk control through data models has also expanded the sales space of the industry.

For example, in the retail credit scenario, banks need to quickly identify and quantify customers' repayment ability and willingness to repay loans based on customer demand for online second-to-second loans, and approve loans.

China-Singapore Jingwei: How to ensure data security?

Wang Feng: Data security includes two aspects: one is the security of the data itself, which prevents the data from being illegally obtained or destroyed; The second is the security of the use of data, to ensure that the data is correctly used under the premise of legal compliance.

In fact, data security and compliance in the financial industry are highly regulated, and companies need to comply with relevant laws and regulations to ensure that the process of data collection, storage, management, and use is compliant. In addition, different countries and regions also have certain requirements for data security, and Chinese companies will also encounter regulatory compliance requirements when going overseas.

(For more reporting clues, please contact the author of this article, Wei Wei: [email protected]) (Sino-Singapore Jingwei APP)

(The views in the article are for reference only and do not constitute investment advice, investment is risky, and you need to be cautious when entering the market.) )

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Editor in charge: Xue Yufei and Li Zhongyuan