As for the industry, on April 1, 2017, the State Council released the document on the establishment of Xiongan New Area, stimulating the continuous rising of related concept stocks. On the opposite, remarkable declines were seen for stocks in SEM and GEM. The 10-90 Rule of the market was seriously aggravated. In June, the A-share was include into the MSCI Index. Though no remarkable response was witnessed in a short term, the long-term vision was promising. As for the funds, though the Central Bank still adopted the prudent monetary policy mainly focusing on the financial risks. The funds in the market were still not abundant. In the first quarter, several interest arbitrage events occurred related to insurance funds in the market. The CSRC enhanced supervision on falsification and fought back against insider trading. The CSRC also worked with the CIRC to prevent such arbitrage by insurance companies. With this regard, the influence on market funds was further extended to 2017Q2. Generally speaking, in 2017Q2, the trading volume was low, there're not sufficient hot topics in the market and the growth scale of new investors was relatively low.
As for the mobile terminals, comparative growth on moving base of active users in China’s securities service application market was lowered to -10.67% in April 2017, and the fluctuation range of such growth in May and June 2017 was not remarkable. As for active users, the trends of the scale of active users and new investors in 2017Q2 were still consistent.
According to the data in the Scale of Active Users of APPs Operated by Securities Institutions in China in 2017Q2, among the APP services provide by the Top 10 Securities Institutions, Zhangle Caifutong ranked top with 6.966 million active users, followed by Ping An Securities (4.52 million) and then Guotai Junan (4.303 million). Shenwan Hongyuan Yingjia Financing was ranked in Top 10 for the first time.
In 2017Q2, all major securities institutions securities institutions enhanced input on software development and attached more importance on customer experience and production interaction abilities while enriching the financing services. For example, Zhangle Caifutong upgraded the reverse repo transaction services on national debt. Guotai Junan Junhong added user appropriateness matching process in the purchase of financing products. Ping An Securities made more efforts on product performance optimization. For example, sign-in function was added on the first page, reminding was made to the customer for new products. In addition, several individualized financing products were launched, all-round personal financing services were provided, and the navigation of the entire site was restructured. Functionally, fund gambling function was provided to make real-time tracing on the major products.
As for the comparative growth on moving base, Xiaofang, Ping An Securities and Guotai Junan Junhong ranked top 3 in sequence for active users in 2017Q2. Zhiyuan Yihutong, Zhangle Caifutong, Haitong e-Haitongcai witnessed negative growth this quarter.
In 2017Q2, Xiaofang optimized several details and newly added auxiliary analysis tools such as decision-making signals, which attracted users from other APPs to some extent. Ping An Securities still maintained rapid growth with a relatively large customer base. In this quarter, Ping An Securities upgraded the data center to enable the investors to get latest information of Shanghai-Hong Kong Stock Connect and Shenzhen-Hong Kong Stock Connect. Topics function was newly created to facilitate communications among the users. In addition, welfare sector was renovated to have the customers conduct financial transactions in a recreational manner. With several revision measures, Ping An Securities witnessed relatively great growth rate on user scale in 2017Q2. Zhangle Caifutong had relatively large user scale, and major securities institutions intensified research and development on APP ports, which diverted its users to some extent. Therefore, Zhangle Caifutong witnessed negative growth on user scale. However, its customer loyalty was still relatively great.
Mobile APP port is an important competition arena among the securities institutions and even between the securities institutions and third-party platforms. According to the overall dynamics of this quarter, by upgrading of APPs, the APP-based performance such as new customer and activeness was expected to be further enhanced.
Description on Upgrading of Analysys Qianfan A3 Algorithm: Analysys Qianfan A3 Algorithm applies machine learning approach to make its data more accurately reproduce the actual behaviors of the users and enable product valuation assessment in a more objective manner. The upgrading to the entire algorithm involves the overall process of data collection, cleaning and computation:
1. Collection Side: The SDK is upgraded to adapt to the open API of Android 7.0 and higher; machine learning algorithm is adopted to upgrade the filtration algorithm of “Non-user Subjective Behavior”, which avoids mistakenly elimination while providing more accurate recognition.
2. Data Processing Side: By machine learning algorithm, data completion algorithm is enabled for fragmented behaviors of the users, the equipment uniqueness identification algorithm is upgraded, filtration algorithm o abnormal equipment behaviors is increased, etc.
3. Algorithm Model: External data sources are introduced and integrated with Analysys's owned data for mixed data sources, AI algorithm robots are trained and adjustments are made on algorithms of some indicators.
For more information about the securities service application market, please keep an eye on Analysys's official WeChat account or call at 4006-515-715 for customer services.
Research Notes:
Industrial analysis provided by Analysys is made mainly based on macroeconomic industrial data, final quarterly user survey data, historical data of the companies, quarterly business monitoring information of companies, etc. by Analysys's industrial analysis models with reference to market research, industrial research and company research approaches. And such analysis mainly reflects the market status quo, trends, break points and rules as well as the development status quo of companies.
Analysys believes that the data drawn according to the abovementioned industrial research approaches is within the recognized acceptable error range within the industry and can accurately reflect the industrial trends and change rules.
Such research outcomes made based on professional research approaches aim to provide decision reference. For the actual data of a specific company, please refer to the financial reports released by that company.
Analysys Overview:
Analysys is a leading big data analysis company in the Chinese market. Since the establishment, Analysys has established the big data and analysis service ecological system cored by massive digital user assets and algorithm models.
Analysys has been dedicated in providing product services such as digital user portraits and competition analysis and assisting in product operation for enterprises; and assisting enterprises in increasing revenues, saving expenditures, increasing effectiveness and evading risks by operation and management on digital user assets of the enterprises. The products in Analysys Family include Analysys Qianfan, Analysys Fangzhou, Analysys Wanxiang and Analysys Boyue. By June 30, 2017, Analysys had covered 2.07 billion intelligent terminals and monitored over 2.05 million mobile APPs.