Large model, computing power, cloud usage, independent innovation. In 2023, these words have become the focus of attention in the digital transformation process of all walks of life. The same is true for the financial industry, which has always been at the forefront of digitalization.
As the "vanguard" of digitalization, the financial industry has moved from digitalization to the era of digital intelligence. Under the guidance of market demand and industry norms, cloud computing provides more and more important basic support for the digital and intelligent transformation of the financial industry. According to the report "China Financial Cloud Market (First Half of 2023) Tracker" recently released by the International Data Corporation (IDC), China's financial cloud market has achieved significant growth in the first half of 2023, with a year-on-year increase of 278%, showing good market development health.
The use of cloud in the financial industry has shifted from "whether to use" to "how to use it well", and in recent years, many cloud service providers have gradually increased their application practices in the financial field.
As we all know, the financial industry has extremely high requirements for digital technologies and products, and with the development of various digital technologies in recent years, the digital and intelligent transformation of the financial industry is ushering in broader opportunities and facing more challenges.
With the rapid development of digital technology, the digital transformation and upgrading of finance continues to accelerate. The use of some new technologies, such as cloud computing, distribution, big data, microservices, etc., as well as the use of new Internet architecture to support the business development of the financial industry, will improve the overall scientific and technological capabilities of financial institutions, and more effectively promote the financial sector to help the real economy develop in depth. "At the same time, in recent years, driven by relevant policies, various financial institutions are trying to migrate business scenarios to localized platforms. Zhang Jin, general manager of the financial technology department of Shenzhou Information, once said in a dialogue with Titanium**.
According to the report "China Financial Cloud Solution Market Research (2022)" released by Frost & Sullivan, an international authoritative analyst, the financial industry is facing huge challenges and opportunities for digital transformation in recent years. Practicing cloud-native thinking and practice, and realizing digitalization and intelligence have become the key to the success of transformation.
In the face of the new era of digital intelligence, the financial cloud can be said to have entered an era of change.
Cloud native, one cloud with multiple cores, continuous evolution, open ecosystem, security compliance, and independent innovation have become the key development directions of financial technology.
Taking banks as an example, the IT architecture of banks can be divided into four stages, namely, the "stand-alone era", "the era of online networking", "the era of big data centralization", and the "distributed and cloud-native era" in which the industry is currently located. How do you ensure security compliance in this process?How to achieve independent innovation?How Do I Smoothly Migrate Legacy Data to the Cloud?How to achieve stability and reliability?Even, how to achieve intelligence?Many problems need to be solved by financial institutions and cloud technology providers.
At this stage, for the vast majority of enterprises, 60% and 70% of the data within the enterprise are not used, if the enterprise can use this part of the data, these data will further drive the business development of the enterprise, "Most enterprises do not have data-driven capabilities, resulting in the current situation of insufficient enterprise data application, but compared with data application, there are more enterprises that lack data governance capabilities." This has become a common "pain point" for enterprises in all industries.
The above pain points also exist in the process of digital and intelligent transformation of the financial industry, so data governance is one of the main challenges faced by financial institutions. How to effectively integrate the data in the original minicomputer and x86 server with the heterogeneous data in the cloud to achieve unified management and unified call is the first problem that the financial industry needs to solve. Data governance plays an important role in improving the accuracy of business decisions, risk control, and customer satisfaction.
Before becoming data-driven and data governance can be achieved, the characteristics of the financial industry determine that it is necessary to build the most solid data security foundation.
In the financial industry, which has a high demand for security, compliance, and independent innovation, an independent innovation and fully trusted database is an indispensable key for financial institutions to move from data governance to data-driven.
It is reported that through the cooperation with HUAWEI CLOUD, ICBC has broken through the main technical bottlenecks and implementation obstacles in database transformation by using HUAWEI CLOUD GAUSSDB, not only realizing the 7*24-hour service continuity of the core financial system, but also building a data service system with full-scenario support capabilitiesBy integrating HUAWEI CLOUD GaussDB with ICBC's IT architecture system, it implements end-to-end cloud-based resource scaling capabilities and connects the database with the entire lifecycle process of application R&D.
It is understood that ICBC's credit system used Oracle before, and there were 15 to 30 minutes for park-level failures in the same city, and only 180 seconds for smooth transfer to GAUSSDB, which is a qualitative leap. Recovery Time Objective (RTO), also known as Recovery Time Objective, is a time window that indicates the maximum acceptable time for business or service interruption.
According to statistics, more than 50 financial institutions have chosen GaussDB since HUAWEI CLOUD released the next-generation GaussDB database in June this year. At the same time, Zhang Xiuzheng, Vice President of Huawei and President of HUAWEI CLOUD China, introduced at the HUAWEI CLOUD Industry Summit 2023 Financial Industry Forum held on November 30: "The GaussDB database has been successfully verified in multiple scenarios in conjunction with major banks such as ICBC, China Merchants Bank, and CCBWhen it comes to carrying the core system, GaussDB's high availability, security, and high performance capabilities are far ahead of similar products in the industry.
Zhang Xiuzheng, Vice President of Huawei and President of HUAWEI CLOUD China.
It is understood that Huawei has developed a complete set of independently innovated and fully credible software development pipelines, providing end-to-end lifecycle capabilities from project management, IDE, development to deployment. Based on this software development pipeline, HUAWEI CLOUD GaussDB database can provide financial institutions with a database with high availability, high security, high performance, high elasticity, high intelligence, easy deployment, and easy migration, meeting all the requirements of financial institutions for databases, and helping financial institutions implement business scenarios safely and quickly.
As financial institutions continue to improve data governance and enhance the level of independent innovation to ensure data security, the next issue is how to use cloud technology to stimulate the greater value of this data and make data drive business development.
First, as the volume of data in financial institutions grows, data integration and standardization become even more important. Financial institutions need to establish a unified data model and standardized data system, and integrate different types of data to improve data processing efficiency and data quality.
From the perspective of data architecture, taking banks as an example, the original architecture is vertical and chimney-like, which makes it difficult for data to circulate, and the "elasticity" of the chimney-like architecture is also very poor, which does not meet the higher demand for digital architecture flexibility put forward by banks with the rapid growth of business.
In order to solve the problems of poor elasticity of traditional architectures and low efficiency of data development, cloud service providers have also proposed practical solutions through active research and development. Taking HUAWEI CLOUD as an example, HUAWEI CLOUD has launched the HUAWEI CLOUD Digital Intelligence Convergence Platform through software and hardware collaboration and architecture innovation, which adopts a pooled architecture that separates storage, cache, and computing, and enables data to be freely shared among data lakes, data warehouses, and AI through converged data management and converged data acceleration, making data usage more agile. At the same time, due to architecture-level innovation, the performance of storage and computing separation is close to that of storage and computing integration.
For users, HUAWEI CLOUD's digital intelligence convergence platform provides a data + AI convergence workbench to achieve seamless collaboration between DataOps, MLOPS, and DevOps, lowering the threshold for data and model development and O&M. In addition, the HUAWEI CLOUD Digital Intelligence Convergence Platform uses AI4Data to implement full-link intelligence for data development and governance, improving the efficiency of data development and governance by two times.
Through the current trend of financial institutions in data-driven, it can be seen that data integration and standardization, data mining and modeling, real-time data analysis and application, data visualization, and data security and privacy protection have become important trends for the future development of financial institutions. Through data analysis and mining, financial institutions can better understand market demand, optimize product design and service models, and improve risk control capabilities and operational efficiency.
The big model will reshape all industries" - this seems to have become the consensus of all industries at present. As mentioned above, with the support of the new generation of AI technology represented by large models, the financial cloud has also entered the era of comprehensive intelligence. In the data-driven process, financial institutions are also trying to explore the use of large models to empower business development and accelerate the release of data value. Although the development of industry-level large models is still in its early stages, HUAWEI CLOUD has a targeted layout in this regard.
In HUAWEI CLOUD Pangu large model 3In version 0, based on the Pangu L0 model, HUAWEI CLOUD has strengthened the security assurance of financial knowledge, skills, tools, and full-process models, and integrated financial industry datasets to create the L1 industry model, Pangu Financial Model, which provides industry solutions based on the Pangu L0 basic model, including knowledge retrieval middleware, recommendation middleware, data analysis middleware, writing middleware, and coding middleware.
The intelligent financial cloud can also improve the risk control capabilities, operational efficiency, and service quality of financial institutions, and also reduce the IT costs and thresholds of financial institutions, providing strong support for the digital transformation of financial institutions.
AI can help financial institutions better assess and manage risks. By analyzing a large amount of historical data and real-time information, it can provide more accurate and timely risk management decision support for financial institutions by evaluating market risk and credit risk. This will help financial institutions reduce risk and increase profitability.
In this regard, Zhang Xiuzheng said that in order to better promote the full embrace of intelligence in the financial cloud, HUAWEI CLOUD has cooperated with more than 20 financial institutions in more than 10 fields and more than 50 application scenarios since the beginning of this year. Through these collaborations, we see that large models have had a profound impact on the financial industry and are changing the way every financial business operates, as well as the consumer experience. Zhang Xiuzheng pointed out.
Taking ICBC as an example, HUAWEI CLOUD worked with ICBC to optimize the intelligent customer service based on the large model, reducing customer call time by 10% and improving service efficiency by 18%, while enabling all users to enjoy the same inclusive financial services.
It is understood that Huawei and Bank of Communications have jointly established an artificial intelligence joint innovation laboratory, which will build an expert-level assistant based on the Pangu model to improve internal operational efficiency and achieve precise financial risk prevention and control.
Coincidentally, Han Man, General Manager of the Distributed New Core Business of Huawei's Digital Finance Corps, also shared with Ti** that a city-level commercial bank has adopted a smart operation system to integrate the capabilities of large models into the system, handing over about 70% of the workflow to artificial intelligence, and only retaining nearly 50 employees for review work, improving the overall audit efficiency.
Of course, even under the general trend of intelligence, security and reliability have always been one of the most basic and core requirements for cloud products and solutions in the financial industry. With the advent of the era of comprehensive intelligence, while improving the efficiency and quality of services, financial institutions can also further improve security through data encryption, access control, identity authentication, intelligent monitoring and other means.
As a cloud that focuses on the financial industry, HUAWEI CLOUD has served more than 500 financial institutions around the world, including China's six major state-owned banks, 12 joint-stock commercial banks, top 5 insurance institutions, and 7 top 10 companies.
It is worth mentioning that according to the China Financial Cloud Market (First Half of 2023) Tracker report released by IDC, HUAWEI CLOUD Stack ranks first in China's financial self-built dedicated cloud infrastructure market, which is also the first place in HUAWEI CLOUD for the year.
In addition, Frost & Sullivan, an international authoritative analyst firm, released the "China Financial Cloud Solution Market Research (2022)" report, which tracks and evaluates the financial cloud solution market and trend direction. According to the report, in 2022, HUAWEI CLOUD ranked first in the overall evaluation of three innovative solution capabilities: financial distributed core upgrade, financial intelligent data lake, and financial cloud native infrastructureAt the same time, it also won the first place in five markets, including financial cloud platform, financial dedicated cloud platform, financial cloud big data, financial cloud native database, and bank cloud, and its capabilities and markets are in the leading position in the industry.
In the era of fully intelligent cloud, only by adopting an open and co-creation attitude, win-win cooperation with upstream and downstream enterprises in the industry, adhering to the spirit of "craftsman", deeply cultivating the financial industry, and constantly innovating and making breakthroughs, can China's financial cloud achieve high-quality development.
(This article was first published by Titanium **app, author |.)Zhang Shenyu, editor |Gai Hongda).