Banking management transformation big trend
Song Yu Chang Liu Zhen
Editor's note: Along with network technology, all industries such as banks, securities, insurance, taxation, etc., pay great attention to the purpose of strengthening centralized management through data concentration. This newspaper published on April 9, the article discussed in the data concentration of tax industries caused the extensive resonance of readers. This issue will continue to pay attention to the problem of data concentration in the banking industry. In the middle of the 1980s, my country's banking electronics is basically in the main stage of stand-alone operations in the microcomputer. In the mid-1990s, large commercial banks basically realize data concentration in the prefecture-level city, and a few commercial banks have begun. In implementing data concentration in province, some commercial banks have even considered data concentration in a larger range. Therefore, bank data concentration has become a big trend in the development of the banking industry in the new century. The trend in data concentrations and the development of advantageous data are managed to the development of the banking industry. At the same time, network technology is increasingly maturing and providing conditions for achieving data centralized management. The advantages in data concentration are reflected in the following aspects: 1 Make cross-regional financial transactions more quickly, and more reliable, the distributed processing system under Wide Area Network still has problems such as transaction, reliability, etc., although the development of network hardware technology, this situation has changed, but how to ensure two places Data consistency still has no practical technology solutions. Take the traffic of cross-regions as an example. When handling the deposits of the payment, accepting a row to charge or pay cash, and record the funds clearing status of the agency in the local host, and open an account (by the agency It is necessary to correct the savings balance of the house in time. If one is successful, one party fails, resulting in inconsistency, resulting in business errors; at this time, it is necessary to pass the query operation (some system implementation automatic query) confirm the host, and Fixed the corresponding data corresponding to the host. When the network communication quality is relatively low, the data is inconsistent. From the current state of technical conditions, only the data centralized processing can guarantee the timeliness and reliability of the transaction. 2. In the environment where customers focus on market intense competition, banks have transformed customer service as a business focus, and transformed from the old system's accounting center mode to the customer center mode. In today's personal or enterprise, its socialization is increasing, the demand for financial services across regions has increased, new banking services, such as PC banks, family wealth management, telephone banks, online banking, etc., such as spring, spring, spring. In a distributed system environment, it is difficult to achieve cross-regional customer service, especially in the case of multiple areas, providing unified customer services under distributed systems. Taking customers-centered implementation models, banks require banks to link different accounts from the same customer, and timely master customer fund dynamics and flow. Therefore, only data concentration is handled, in order to make the customer-centric business thinking, it is achieved in a greater range, and it is based on the competitiveness. 3. Implement centralized management, reducing financial risk banking is based on service types. The management model of this block segmentation has not adapted to the requirements of enterprise reform, and it is more unable to adapt to the requirements of the information age. Nowadays, banks are all intended to operate the road, and the business is reflected in the "General Meeting" model. From the horizontal direction, it is to break the existing savings, accounting, credit card and other business division, form a unified comprehensive teller system; from portrait It is to form a unified management of all branches of the bank to achieve the purpose of preventing financial risks and improving corporate efficiency. To reach the above objectives, the data must be highly concentrated. After the data is concentrated, you can effectively manage the reports, customer information, and various data resources of the branch, and eliminate the fake accounts, the form, the fake data, and ensure the authenticity, consistency, integrity of statistics. And accuracy. 4. Missing the pressure bank of the stressed bank of science and technology personnel always requires a certain number of scientific and technological personnel maintenance, and some areas require a significant number of software developers to expand their business and develop new business processing systems. In the distribution system, all levels must organize a certain number of scientific and technological personnel to do system maintenance, and personnel waste is only one aspect. More importantly, in some areas, it is difficult to have qualified maintenance personnel, from China to abroad, computer Professional talents are quite scarce, only data concentration can concentrate on scientific and technological talent power, and achieve the most effective use of human resources. 5. It is conducive to data mining and analysis in traditional bank business behavior, and the data available to analyze decisions is relatively small, such as savings balance, balances, etc., the lack of decision-making data, will inevitably lead to a certain blindness of management decisions . In the business system, a large number of historical data has been accumulated. These historical data have a great help, but due to the large amount of data, the data analysis means are backward, the data is widely distributed in different processing hosts, so that these historical data is flooded Drop. The next step in the data set is to utilize relevant technologies such as data warehouses and OLAP to implement data mining and provide decision-making support.
