Title: Li Chenxi

Editor: Zhang Jing

Source: Finance Mayflower

Image Source: Generated by Wujie AI

Before dawn is an exciting moment.

In 2023, the Chinese economy is undergoing a process of recovery and rejuvenation. The performance of the banking industry is a reflection of this. The financial report season for listed banks has just passed, and the data shows growth in profits and stable asset quality. The hidden reefs that lie ahead are also faintly discernible: where will the effective credit demand come from, and the AI technology revolution brought by large models is quietly descending at unexpected moments…

"At the Bund Summit Banking Digitalization Forum, guided by the China Banking Association and organized by Webank, Ant Group's Senior Vice President and Chairman of Webank, Jin Xiaolong, expressed on-site that the core driving force behind the development of banks is undergoing a change. Previously, it was scale-driven, but now it is driven by new technology." He stated that China has already formed global competitiveness in bank digitalization: there have been significant changes in the touchpoints of bank operating services, the form of bank products, the core driving force of bank growth, and the operating philosophy of banks.

Change breeds trends, and trends represent opportunities. A survey conducted at the forum targeting over 200 banking technology practitioners showed that over 90% will increase investment in AI technology, and nearly 80% believe that banks will apply large models and will be implemented within 1-3 years.

Digitalization, the new battlefield for banks

"As a long-time banking practitioner, we have seen that before digital transformation, extensive growth based on casting a wide net and pursuing scale was the mainstream. After digital transformation, precise marketing, refined management, and precise operations based on big data have become the direction for the upgrade of banking institutions. Now, finance is technology, and technology is finance. Large models, cloud computing, and the Internet of Things are 'new technologies' that have become the new battlefield for leading institutions," said Jin Xiaolong.

After researching banking digital technology, IDC China's Vice President and Chief Analyst, Wu Lianfeng, summarized the current five major trends:

The first trend is mobile banking. The "2022 China Banking Industry Service Report" shows that the average electronic diversion rate of banks is 97%, and over 90% of the business has been realized online. A third-party data monitoring platform shows that by the end of June 2023, the monthly active users of mobile banking apps in China exceeded 500 million. Not only apps, but banks have also developed over 200 mini-programs on WeChat and Alipay.

Mobile banking is making banks more and more like "internet companies." By the end of 2022, the Industrial and Commercial Bank of China had 174 million monthly active app users, comparable to many leading internet companies. China Merchants Bank has also integrated many lifestyle services into its app, including dining services, movie ticket purchases, and travel services.

The second trend is AI risk control. IDC predicts that by 2026, applying artificial intelligence to credit granting will become the mainstream choice for banks. Due to the application of more complex models and algorithms, by the end of 2026, cases of bank fraud and money laundering will decrease by 12%.

AI risk control has already been explored in the banking industry. For example, Webank's Bailin intelligent interactive risk control system applies large-scale artificial intelligence to microfinance. It serves as an AI credit approval officer, where users submit contracts, invoices, and other materials, and the AI credit officer uses computer vision, multimodal recognition, and human-computer interaction and other AI technologies to conduct online reviews and complete credit increases. It has already served 8 million micro and small business owners.

China CITIC Bank's "Sentinel" intelligent anti-fraud risk control system applies machine learning and big data technology to anti-fraud. Throughout 2022, "Sentinel" actively dissuaded over 800 fraud victims and intercepted funds exceeding 100 million yuan.

The third trend is digital employees. IDC predicts that by 2025, over 80% of banks will deploy digital personnel, responsible for 90% of customer service and financial consulting services. With the implementation of large models, digital employees "understanding text, understanding language, and understanding business" will become the norm.

SPDB was the first bank to "hire" digital employees. The 3D digital employee "Xiao Pu" has "worked" in over 20 positions, including wealth planners, document reviewers, lobby managers, and phone customer service. "Jiao Jiao" and "Xiao Jiao" are digital employees at Bank of Communications. They can not only answer customer questions but also serve as a technological brand.

The fourth trend is edge IoT. IDC predicts that by 2027, 40% of G2000 companies will use low-orbit satellite technology to fill the network coverage gap in remote, rural, and high-risk areas. With the help of AI IoT technology and other data, the loan coverage rate for small and micro-enterprises in various industries will reach 70%.

Ping An Bank has launched three satellites in succession and built the "Star Cloud IoT Platform." Real operating data of upstream and downstream enterprises in the supply chain can be transmitted back more timely and effectively, thereby facilitating credit granting. As of the end of June 2023, the Star Cloud IoT Platform has supported financing for physical enterprises exceeding 800 billion yuan.

Webank's Dashaque satellite remote sensing risk control system applies satellite remote sensing technology to rural finance, providing precise credit and reasonable repayment periods for rural households. Dashaque has served 1.2 million operating households. In data-sparse rural areas, it has found a new technological path to solve the issue of "whether there is" financial services.

The fifth trend is cloud-native architecture. IDC predicts that by 2025, 60% of banks in China will formulate and implement a cloud-native digital core strategy based on the current usage status of applications.

In addition to Webank and WeBank, other technology banks, state-owned banks, joint-stock banks, and city commercial banks have also accelerated deployment. China Guangfa Bank has been building a container cloud platform since 2019 and has attempted to connect 223 applications. After migrating to the cloud, Guangfa Bank's IT costs have significantly decreased, with CPU savings exceeding 43.54% and memory savings exceeding 65.12%. At the same time, the efficiency of new application development has greatly improved. Construction Bank has even established "CCB Cloud," entering the cloud computing business and launching the first three categories of 10 cloud service packages, providing "ready-to-use" technical services for small and micro financial institutions.

AI benefits more ordinary micro-enterprises

"The financial industry is one of the most suitable fields for the application of artificial intelligence technology, including large models," said Sun Maosong, Deputy Dean of the Institute for Artificial Intelligence at Tsinghua University.

Seizing the opportunity has become an industry consensus. A survey targeting over 200 banking technology practitioners showed that over 90% will increase investment in AI technology, and nearly 80% believe that banks will apply large models and will be implemented within 1-3 years.

Change has already begun. From a global perspective, in the banking business sector, Bank of America's virtual assistant "Erica" helps customers refine asset reports, track consumption, and provide personalized advice. In the field of financial security, MasterCard uses AI technology for fraud detection to avoid losses. In personalized financial services, fintech companies such as Wealthfront and Betterment use intelligent robot wealth management platforms to provide users with personalized and customized financial advice. It is worth noting that regulatory technology (RegTech), such as European banks, has already used AI technology for regulatory aspects such as anti-money laundering and intellectual property protection.

China's exploration is equally impressive, even going further, with the use of AI technology in investment strategies, risk control, and intelligent customer service. For example, Feng Liang, the president of Webank, stated that in the eight years since its establishment, Webank has not had a single branch or credit officer. With over 1,600 employees, more than half of whom are technology personnel, it has served over 50 million micro and small business owners, covering cities and rural areas across China. This customer base is the largest globally.

The satellite remote sensing risk control system, the supply chain finance solution Dayan system, and the Bailin intelligent interactive risk control system, three technological birds, constitute the intelligent risk control system of Webank. "Without AI technology, the number of users that 1,600 employees can serve would at most reach the million level. But with the application of AI, the breadth and depth of financial services have been expanded, allowing users who were previously uncovered to be covered as well."

Feng Liang believes that AI is transforming thousands of industries, and it can even be said that the entire industry will undergo a paradigm shift because of technology, especially artificial intelligence technology in the future. In fields with high potential demand and scarce human experience, there is greater room for AI to play a role.

Artificial intelligence is not meant to replace people, but to develop and liberate people. "Let's imagine that when large models have the same accuracy in medical diagnosis as authoritative experts, and when the teaching ability of large models is comparable to the best teachers, more ordinary people can enjoy top-notch medical care and education. This is the value of artificial intelligence. Webank will continue to explore the application of large models and AI, allowing digital financial services to benefit more ordinary micro-entrepreneurs," Feng Liang said at the Bund Summit.

Of course, it is worth noting that the real landing application of large models and leading paradigm shifts still takes time. Sun Maosong, Deputy Dean of the Institute for Artificial Intelligence at Tsinghua University, believes that general large models need sufficient training with financial industry data to truly unleash their value. Therefore, banks need to establish a strong and efficient vertical team for large model technology, deeply integrate internal needs, and train general large models to create incremental value.

Lin Deming, Vice President of Guangfa Bank, stated that the comprehensive handling of six key elements is required for the digital and intelligent transformation of banks: there must be clear transformation goals and comprehensive strategies; investment from the CEO to middle management; deployment of high-quality talent; flexible and agile governance thinking to drive broader mindset changes; effective progress management and establishment of clear standards; and the need for business-led technology platforms and data platforms to establish a modern technology architecture driven by business needs. Lin Deming pointed out that to deepen digital transformation, banks need to build full-chain digital operational capabilities, end-to-end efficiency measurement capabilities, and full value chain agile collaborative capabilities.

Ultimately, only when the enterprise itself changes can it seize the opportunities presented by technology.

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