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The following is the White paper on key infrastructure of bank data center in Digital Era From Vertiv recommended by recordtrend.com. And this article belongs to the classification: research report.
Financial technology brings innovation to banking business model. The development of financial digitization promotes the rapid growth of data. Customer behavior and business operation data can become valuable intangible assets. Through the development and utilization of mobile Internet, cloud computing, big data, artificial intelligence and other means, it can open up a broad space for the improvement of operation efficiency and service level, so as to gain advantages in the fierce market competition.
In the face of the outbreak of business, it has become a great challenge for the banking industry to ensure the security of financial data, meet regulatory requirements, ensure business continuity, and avoid losses caused by data center downtime. Ensuring the high availability of data center is one of the key elements to ensure the stability of financial business. At the same time, the banking industry actively responds to the call of national energy conservation and environmental protection, and hopes to obtain the new attributes of low consumption, energy saving and efficient deployment under the premise of safety and stability. This white paper will focus on the analysis of data center application scenarios and corresponding key infrastructure solutions for the banking industry.
1、 Opportunities and challenges faced by the banking industry in the digital era
1. Rapid growth of business in the era of mobile Internet
After entering the era of mobile Internet, the number of users and transaction frequency of mobile terminals have increased significantly; customers require that they can query and process banking business anytime and anywhere; mobile payment and Internet payment are more extensive and convenient; more and more third-party systems are connected to banks, all of which lead to the rapid growth of financial business. In addition, big data and artificial intelligence are widely used in risk control, marketing assistance, quantitative investment, intelligent investment advisory, risk identification and other fields. These not only provide strong support for digital finance, but also lead to explosive growth of data.
Many third-party payment systems not only bring massive business to banks, but also bring great pressure to the banking system. For example, “double 11” and other transaction peaks not only pose new challenges to the e-commerce platform, but also to the processing capacity of the core system of the bank, because the final correctness of the transaction depends on the banking system to ensure.
2. Banking supervision is increasingly strict
In recent years, the national regulatory authorities have put forward higher and higher requirements for the security and controllability of the banking system. Financial regulatory compliance review involves many business systems, and traditional manual operation will cost a lot of time and labor cost.
3. Increasingly demanding business continuity requirements
Banks have extremely strict requirements for the continuity of important business systems. If large commercial banks shut down for more than half an hour, the indirect loss of business and reputation can reach hundreds of millions of yuan, and there is a trend of rapid increase year by year.
4. Cross border competition from Internet companies and public opinion pressure
In recent years, banks are facing increasingly fierce cross-border competition from Internet companies. These Internet companies try to embed more and more financial services into their existing businesses, so as to increase the stickiness to users and obtain user data with strategic value. Therefore, it is easy for the public to make a simple comparison between Internet companies and banks, and the high expectations of the society for the technological innovation of banks have brought huge public pressure on banks.
2、 Distributed architecture and centralized architecture
For the bank core system, the importance of transaction data consistency is self-evident. In the current financial system business reliability requirements and regulatory conditions, “final consistency” program in the banking industry also faces many challenges.
Finance has the requirement of strong real-time consistency for data business. Centralized relational commercial database is used to meet acid (representing atomicity atomicity, consistency consistency consistency, isolation isolation isolation and durability persistence), which is the foundation of realizing strong real-time consistency.
Based on the current technical level, the core business of banks can not get rid of the dependence on centralized database architecture, which is one of the main reasons why the it cost of banks is much higher than that of Internet companies. For example, a mainframe or minicomputer used to host a centralized database is much more expensive than an X 86 server cluster.
At present, the feasible bank distributed architecture is actually a hybrid mode. In the core database, due to the requirements of business continuity and data “strong consistency” and the constraint of cap principle, it is difficult to realize complete distributed processing, so the centralized architecture is still adopted.
For core business, such as deposit, loan, payment, value-added, etc., under the requirement of strong real-time consistency of data in current business process, the core business of most banks adopts centralized architecture.
For the Internet application scenarios with external collaboration such as electronic channel, the application of distributed architecture can be considered because of the support of core system. In addition, applications that do not require high real-time consistency of data, such as data analysis, internal management, big data credit reporting, big data marketing, big data risk control, can also adopt a distributed architecture.
For Internet companies, the unit data value of their main businesses (social networking, search, e-commerce) is low, and they are used to the lowest TCO operation (TCO total cost of ownership = capex initial investment cost + OPEX operating cost). They do not require high real-time consistency of data, and they can also accept the “final consistency” of data. Therefore, the open distributed architecture is widely used to realize the flexible expansion of database and even the redundant backup of cross region (Data Center).
Internet companies and banks are totally different in business logic, regulatory methods and data requirements, which also leads to different technology choices. Distributed database and centralized database have their own advantages and disadvantages, and they play the platform advantages in different matching fields.
3、 Innovation direction of bank data center
In order to reduce the risk of excessive concentration of core business in a single master data center, weaken the interaction between businesses, so as to achieve the separation of core business deployment, is the mainstream construction idea of bank core data center in the next few years or even longer. For non core business and application layer software, distributed architecture can be considered.
Since the guarantee of bank’s core business continuity and data consistency rests on the core data center, the availability / reliability of these core data centers can not be reduced, but must be strengthened. So, the question is: how to ensure high availability?
Data center should put forward appropriate data center availability requirements according to business importance. According to the statistical results, power supply and refrigeration account for only 5% of capex in the data, but they are very important to ensure the reliable operation of the data center, so the investment in power and environmental equipment has a very good availability cost-effectiveness ratio.
The failure of key data center will bring huge direct loss and immeasurable indirect loss (reputation, etc.) to banks. According to the research of Ponemon Institute, a third-party research organization, the average cost of downtime for bank data centers is as high as $994000 per time.
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