2020 5th International Conference on Social Science and Management (ICSSM 2020) ISBN: 978-1-60595-675-6

Research on Competitiveness of Shengjing Bank under Factor Analysis Ye-Qing LIU1,a and Wen-Bing BAO1 1Nanjing University of Science and Technology, Nanjing, Jiangsu, [email protected]

Keywords: City Commercial Bank, Shengjing Bank, Bank Competitiveness, Factor Analysis.

Abstract. Since 2017, the world economic environment has changed profoundly, and Chinese city commercial banks, especially Shengjing Bank, have been deeply affected by it. Therefore, Shengjing Bank's 2018 interim report states that it is necessary to comprehensively strengthen risk management, to innovate intermediate businesses and other business structures, and improve Bank's overall competitiveness. In order to compare the competitiveness level of Shengjing Bank in recent years, this article selects 23 city commercial banks as reference objects, and intends to use the factor analysis method to use Spss software to collect the 13 financial indicators of 24 city commercial banks from 2015 to 2017. Comprehensive analysis of the data, taking into account the indicators of all parties, draw conclusions, and give specific suggestions for the problems existing in Shengjing Bank. The study found that the competitiveness level of Shengjing Bank did decline in 2017, which should attract the attention of senior management of the bank.

Introduction After the 19th National Congress of the Communist Party of China was convened, the prevention of financial risks has been fully launched, and China's banking industry is facing more severe supervision. In 2018, the City Commercial Bank Development Report pointed out that in recent years, with the changes in the external market environment and economic policy environment, city commercial banks have faced many uncertain factors, resulting in city commercial bank assets and liabilities It has risen, but the growth rate has deferred the downward trend since 2015. The report also pointed out that the city's commercial banks' non-performing loan balance and non-performing loan ratio have also started to "double rise" since 2016, and the return on assets and return on capital have also started Go down. As the earliest and largest city commercial bank in , Shengjing Bank's competitiveness has also shown obvious shortcomings under the dual impact of internal and external environments. In this context, Shengjing Bank needs to continue to innovate with high-pressure policies in order to Adapt to new requirements and further improve your competitiveness.

The Empirical Research This article will use Spss software to perform factor analysis on 13 related index data of Shengjing Bank and the remaining 23 city commercial banks from 2015 to 2017. The factor analysis method can achieve the dimensionality reduction while retaining most of the indicators. In addition to the original information, this method also has the advantage that it can consider some indicators that cannot be measured, explore the basic structure between the observation data by studying the internal dependencies between many variables, and use a few abstract variables to represent the basic data structure, these abstract variables are called common factors. Selection of Indicators Commercial banks have three operating principles: liquidity, security, and profitability. The bank's observable data and reports also revolve around these three core operating principles, and the competitiveness of commercial banks is more in line with these operating principles. Relevant, but unfortunately there is no absolute financial indicator that can indicate the changes and pros and cons

472 of all operating policies, and there is a certain contradiction between liquidity, security and profitability. A balance was reached among the three to maximize the bank's competitiveness. On the one hand, since the city commercial bank is a part of the commercial bank, the index selection in this article is based on the business policy of the commercial bank, and it is of certain significance to select the indicators describing the liquidity, security and profitability. On the other hand, the development of city commercial banks is relatively young compared with commercial banks, so this article also selects some indicators to describe the potential competitiveness of city commercial banks. Therefore, based on the three principles of bank operation, this article scientifically builds a bank competitiveness evaluation index system. The specific indicators are selected as follows: Profitability is the primary policy of commercial bank operation. Obtaining revenue is the basic driving force and purpose of commercial bank's operation and management. This principle also requires urban commercial banks to maximize the benefits if conditions permit. Profitability indicators are undoubtedly a set of variable indicators that are directly related to bank competitiveness. Therefore, this article selects four variable indicators that describe bank profitability from different aspects: Return on capital, Operating margin, Cost to income ratio, Return on other assets. Security indicators can provide solutions and specific control methods for the risk management and control of urban commercial banks, so four variable indicators are also selected: Capital adequacy ratio, Equity ratio, Equity ratio, NPL ratio. Among them, the capital adequacy ratio can directly reflect the bank's ability to withstand external risks, the equity ratio can reflect the size of corporate financial risks, and the statutory deposit reserve ratio is one of the "three magic weapons" for the central bank to regulate macroeconomics, which is important for maintaining the stability of the entire banking industry. It plays a vital role. In consideration of the “double rise” of non-performing loans of city commercial banks in recent years, the index of non-performing loan ratio was introduced to reflect banks' risk control capabilities in terms of loans. The liquidity index reflects the operation of the bank's funds in the daily operation process and is also an important aspect of the bank's daily operation and management. Therefore, two variable indicators are selected for description: Liquidity ratio, Provision loan ratio. The liquidity index directly reflects the liquidity of bank assets, and the provision as a fund occupation will also affect the bank's liquidity to a certain extent. The last is the growth indicator, which describes the growth ability of the city's commercial banks through the percentage change of the main indicators over the three years. A total of three variable indicators are selected to describe the bank's potential competitiveness: Asset growth rate, Operating income growth rate, Net profit growth rate. Empirical Analysis Statistical Data Inspection. The factor analysis fitness test method used in this paper is KMO and Bartlett's test. According to past experience, factor analysis can be tried when the KMO score is greater than 0.5, and the higher the score, the more suitable it is for factor analysis. The second test indicator is the Bartlett's test. If the difference is significant, then reject the original unit matrix hypothesis and consider that the correlation between the original matrices is significant. It is suitable for factor analysis, that is, the difference does not exceed 0.01 and passes the Bartlett's test. The results show that the KMO test value is 0.589. Therefore, the data of 24 city commercial banks from 2015 to 2017 are valid for factor analysis. In addition, the Bartlett's test value is 0, which is less than 0.01, indicating that the null hypothesis is rejected. The correlation between them is significant. To sum up, the inspection indicators have reached the standard. Factor Extraction Analysis of Statistical Data.

473 Table 1. Explain Total Variance. Initial eigenvalue Rotational square sum loading Compone % Of Cumulativ % Of Cumulativ nts Total Total variance e% variance e% 1 3.137 24.127 24.127 2.87 22.08 22.08 2 2.309 17.765 41.892 2.183 16.791 38.87 3 1.699 13.069 54.961 1.996 15.354 54.225 4 1.339 10.297 65.257 1.434 11.033 65.257 5 0.989 7.611 72.868 6 0.924 7.104 79.972 7 0.689 5.304 85.276 8 0.552 4.246 89.522 9 0.471 3.625 93.147 10 0.317 2.439 95.585 11 0.247 1.899 97.484 12 0.18 1.387 98.87 13 0.147 1.13 100 Note: Extraction Method: Principal Component Analysis. Table 1 is a table explaining the total variance. From Table 1, it can be seen that the initial eigenvalue of component number 1 is 3.137, which explains 24.127% of all variance variables in total ingredients. The initial eigenvalue of the component number 2 is 2.309, and the initial eigenvalue of the component number 1 accounts for 41.892% of all variance variables, which is the second-largest component explaining all the variance variables. In summary, the first four principal components can account for 65.257% of all variance variables. The same conclusion can be obtained by considering the lithotripsy diagram, so four common factors are extracted in this paper. Outcome of Practice According to the initial eigenvalues and the view of the broken stone map, this article extracts a total of four public factors named F1, F2, F3, F4. At the same time, F is used to represent the comprehensive score of the bank. The comprehensive score of different commercial banks in different cities and the ranking changes are Table 2. According to Table 2, only the three banks, Jiangsu Bank, Qilu Bank and Ningbo Bank, have maintained their comprehensive rankings in the three years from 2015 to 2017. The other 21 banks have a certain monotonous non-increasing period. This situation is further analyzed in detail.

Table 2. Ranking and Changes of Comprehensive Scores of Different Banks. 2015 2016 2017 2015 2016 2017 Bank name Rank Rank Change Rank Change Bank name Rank Rank Change Rank Change ing ing ing ing ing ing Beijing 11 6 ↑5 14 ↓8 Chaoyang 10 8 ↑2 13 ↓5 Nanjing 13 13 — 19 ↓6 2 2 — 1 ↑1 Jiangsu 19 11 ↑8 10 ↑1 Qinhuangda 9 21 ↓12 4 ↑17 o Qilu 7 5 ↑2 3 ↑2 Tangshan 1 1 — 2 ↓1 Baoshang 6 12 ↓6 6 ↑6 Xingtai 5 23 ↓18 8 ↑15 Hangzhou 20 20 — 11 ↑9 Jinhua 15 14 ↑1 24 ↓10 Huishang 21 9 ↑12 9 — Shaoxing 23 15 ↑8 23 ↓8 Guangzhou 18 18 — 17 ↑1 Huzhou 22 22 — 21 ↑1 Lai Shing 3 16 ↓13 15 ↑1 Wenzhou 16 19 ↓3 22 ↓3 Shengjing 8 3 ↑5 18 ↓15 ningbo 14 10 ↑4 7 ↑3 Suzhou 12 24 ↓12 16 ↑8 Zhejiang 4 4 — 5 ↓1 Tailong Changjiang 24 7 ↑14 12 ↓5 17 17 — 20 ↓3

474 In Table 2, there are eight banks that have not declined in the comprehensive score ranking for three years: Bank of Jiangsu ranked 9 forward in three years. The bank actively uses innovative ideas such as the Internet and cloud data to drive revenue, which has increased its overall score. Qilu Bank and Ningbo Bank belong to the Bohai Rim Economic Circle and the Pearl River Delta Economic Circle, respectively. Because the original economy is still acceptable, the two banks rank high. The focused on cultivating differentiated core competitiveness, so all the rankings rose; there were five banks that did not rise in the comprehensive score ranking in three years: The ranking of Wenzhou Bank continued to decline, which is related to the bank's operating model in Zhejiang in recent years Entrepreneurs in the Wenzhou area are in a transition period when family managers change managers, and there are greater risks. Bank of Nanjing and are both old-fashioned city commercial banks, but due to lack of innovation, they rank relatively low. There were six banks that ranked first in the overall score and then declined. It is quite normal for normal ranking fluctuations to appear in fierce competition among peers, which is conducive to the development of peer competition and the market. However, Shengjing Bank, Jiangsu Changjiang Commercial Bank, and Jinhua Bank is very unstable in the ranking changes, and the rankings have changed by 10 or more degrees. This also reflects the uncertainty of its competitiveness from the side. Obviously, this business model is not desirable. Banks should maintain stable development trend. There were five banks that dropped in overall scores and then rose. Among them, in addition to Baoshang Bank, the other four banks also experienced ranking fluctuations of more than 10 places. Observing the rankings of Shengjing Bank in recent years, it can be seen that its competitiveness level increased in 2016 compared to 2015, and Shengjing Bank's competitiveness level in 2015 and 2016 ranked among the 24 city commercial banks selected. The top 10, but by 2017, its competitiveness level has fallen to a large extent, and the decline ranks as high as 15. It should attract the attention of Shengjing Bank management.

Specific Suggestions for Improving the Competitiveness of Shengjing Bank Improve Bank Operating Performance First, innovation drives revenue improvement: no matter whether it is a young city commercial bank or a long-established city commercial bank, due to geographical restrictions, it is not always possible to gain greater visibility, but the use of the Internet can break such restrictions, so it is necessary to use The online online cloud data of the Internet improves traditional businesses, uses the Internet to actively develop new customers, and provides more customers with more secure and convenient investment and wealth management services based on the network to improve bank development efficiency. In addition, in terms of wealth management business, Shengjing Bank should Business objects are shifting from mid- to high-end customers to ordinary customers, providing more customized and differentiated wealth management products that can meet the needs of ordinary customers, thereby expanding market share. Second, improve the business structure network: On the one hand, in the existing market, city commercial banks must not only maintain their original business, but also develop innovative businesses based on this; on the other hand, because Shengjing Bank's customers are mainly concentrated In the Northeast region, the development of Shengjing Bank is severely restricted by the economic development of the Northeast region. Therefore, Shengjing Bank can set up branches outside the province and increase the bank's popularity. Third, increase non-interest income: With the full completion of China's interest rate liberalization in 2015, the profit point of the deposit and loan spread will further narrow, so it is imperative to increase non-interest income. Shengjing Bank started late in the third-party business with a single variety, and in recent years the development of third-party business has also encountered bottlenecks. Therefore, Shengjing Bank should strengthen the development of intermediate and off-balance-sheet business to bring more reliability to the bank Economic growth point.

475 Strengthening Bank Risk Management As the main customers of Shengjing Bank are concentrated in the Northeast region, there is a problem of excessive loan concentration in terms of loans, which is extremely detrimental to the steady development of Shengjing Bank. On the one hand, it is necessary to reduce the concentration of loans and expand the loan business to areas outside the Northeast; on the other hand, it is also necessary to improve the credit system and continue to strengthen internal control. In terms of the current development trend of China's urban commercial banks, improve the credit system It is already a matter that many city commercial banks have begun to deal with. Improving the system requires banks to use the latest big data system to improve customer information in a timely manner, do a good job of pre-loan approval and follow-up loan work, build a scientific and reasonable comprehensive risk control financial system, and apply a series of risk control products to improve this. The system will undoubtedly improve the risk control capabilities of banks.

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