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Views: 68 Author: Site Editor Publish Time: 2022-03-15 Origin: Site
The banking industry is facing more opportunities and challenges in the digital era. The rapid growth of business in the mobile Internet era has led to a significant increase in the number of users and transaction frequency of mobile terminals, customers demand to be able to inquire and handle banking business anytime and anywhere, and the demand for mobile payment born in various scenarios has led to more and more third-party systems accessing banks, these scenarios not only bring massive business to banks, but also challenge traditional banking systems, and with big data and artificial intelligence widely used in risk With the wide application of big data and artificial intelligence in the fields of risk control, marketing assistance, quantitative investment, intelligent investment and risk identification, it not only provides strong support for digital finance, but also makes it possible to improve the operational efficiency and service level of the banking system.
For the core banking system, finance has the requirement of strong real-time consistency for data business, which requires a centralized relational business database to meet ACID (representing Atomicity Atomicity, Consistency Consistency, Isolation Isolation, Durability Persistence), which is the basis for achieving strong real-time consistency.
Based on the current technology level, the core business of banks cannot get rid of the reliance on centralized database architecture, and the feasible distributed architecture of banks today is actually a hybrid model. For the peripheral business, more distributed is used; in the core database, due to the requirements of business continuity and data "strong consistency" as well as the constraints of CAP principle, it is difficult to realize fully distributed processing, so the centralized architecture is still used. For core business, such as deposits, loans, payments, value-added, etc., under the current business process requirements for strong real-time data consistency, the majority of banks adopt a centralized architecture for core business. As for the Internet application scenarios such as electronic channels and external collaboration, because there are core systems to support them, they can consider applying distributed architecture. In addition, applications that do not require high real-time consistency of data, such as data analysis, internal management, big data credit, big data marketing, big data risk control, etc., can also adopt distributed architecture.
Compared with Internet companies, the latter's main business (social, search, e-commerce) has a lower value per unit of data, and does not require high real-time consistency of data, and can also accept data "final consistency", so it is more widely used open distributed architecture to achieve flexible expansion of database, and even cross-geographic (data center) mutual Redundant backup. Internet companies and banks are completely different in terms of business logic, regulatory approach and data requirements, which also results in different technical choices. Distributed and centralized databases have their own advantages and disadvantages, and each plays a platform advantage in different matching areas.
At present, the mainstream construction idea of bank core data center in the coming years or even longer is still: to reduce the risk of over-concentration of core business in a single main data center, and to weaken the interaction between businesses, so as to achieve separate deployment of core business. According to the scale and function, the construction of bank data centers can be roughly divided into headquarters-level data centers, provincial/municipal branch data centers, branch offices and business outlets. Based on technical standard compliance and industry practice, and taking future business expectations into account, the design and construction of banking data centers should meet the principles of standard compliance, high availability, grading by business, and energy saving.
Among them, the bank headquarters data center carries the core business, and financial institutions including the central bank, large state-owned commercial banks, policy banks, joint-stock banks, postal savings banks and large urban commercial banks should be built with the highest availability and reliability; the bank's provincial/municipal branch data center is the information hub of the banking business in the district and undertakes some local special banking business, and such nodes are in Bank branches and business outlets are mainly responsible for network access and carrying a small amount of localized business such as video surveillance, number calling system, etc., and generally the scale of the server room is not large; bank self-service outlets generally only have a number of ATM equipment and video security, access control and other applications that require network access, which usually require unattended and remote management.
In the tide of digitalization and technological disruption, the development of financial digitalization drives the rapid growth of data, and customer behavior and business operation data can become highly valuable intangible assets. Through the development and utilization of mobile Internet, cloud computing, big data, artificial intelligence and other means, banking institutions are constantly reshaping the business model of traditional banking institutions and creating new business models. The digital transformation of banks not only promotes rapid business growth, but also brings many challenges, and the foundation of their digital finance relies on the construction and transformation of robust and reliable data centers in order to provide guarantees for the improvement of banks' operational efficiency and service levels.