According to data released by China Securities Depository and Clearing Company Limited (CSDCC), the number of new investors rose stably on the whole after a sharp decline in April 2017. In June and July, the turnover and index of A-share market went up; in August, the number of new investors reached 1.512 million, representing a growth of 24.6% on a moving base. In September, this figure wasdropped somewhat.
With a stable growth of currency supply and sufficient fund, the currency market remained stable overall in the 2017Q3. On September 30, the Central Bank of China implemented the policy of targeted reduction of required bank reserve ratio, further safeguarding the liquidity of market fund. From the aspect of market, blue-chip shares got popular among investors from mid-May. CIS300 index presented a continuous growth, driving the stock market to recover after a fall. In September, A-share and B-share indexes recorded new heights within the year. China Securities Regulatory Commission imposed penalties against illegal events, and increased administrative punishment, which contributed to rectifying the illegal acts in the securities market.
On mobile terminal, active users of securities service applications fell by 10.67% in April 2017, and increased somewhat in May. In August, the size of active users reached the maximum level, presenting a tendency similar to the increase of new investors. Overall, the size of active users of securities service applications remainedstable. In absence of the dividends from PC terminal to mobile terminal, the size of active users is fluctuating along with the situation of securities market.
According to data of active users of securities service applications released by Analysys in the 2017Q3, among top10 applications, Zhangle Caifutong ranked first with the advantage of active users of 6.8884 million, followed by Ping An Securities, Guotai Junan Junhong and GF Securities Yitaojin. The applications at the third tier had around 3 million active users, resulting in severe competition for rankings. The gap between Zhangle Caifutong at the first tier and Ping An Securities at the second tier wasbeing narrowed.
Securities agencies facilitate users to explore residual value fully through their self-operated APPs. On the one hand, they provide fund, securities and other wealth management products, and on the other, understand properties and preference of customers, further increasing the profitability. Under such background, all securities agency put forth efforts to develop and research self-operated APPs. They develop some AI products for mobile application, which are popular among investors. From the aspect of intelligent analysis, Zhangle Caifutong launched the similar K-line analysis, which aimed to help investors seek desirable stocks through big data storage and screening technology; Ping An Securities promoted D-signal index and bull/bear market operation analysis, and added probabilistic analysis based on big data storage technology, thus providing richer analysis approaches for customers. Apart from intelligent analysis, all mobile application vendors also launched intelligent investment consultant, intelligent news notification and intelligent wealth management. The mobile terminal of securities have ushered into the intelligent era. Only development of products in line with market demands can help them occupy more market share.
As for the comparative growth on moving base, among the top10 applications in the number of active users, Ping An Securities achieved the highest growth of 27.6%, followed by Guotai Junan Junhong, Xiaofang and Zhongtai Qifutong.
Ping An Securities still sustained a fast growth although it enjoyed a huge size of active users. It is because that, on the one hand, it has strong ability of offline promotion, and on the other, it continues to optimize its online products and bolster user experience. In the 2017Q3, Ping An Securities APP increased such functions as position cost line, follow-up of main chips and money game, etc., upgraded its fellow stockholder community and information center, and optimized homepage experience and news page, all of which could meet the personalized demands of customers; Guotai Junan Junhong supported cloud data storage and review of historical tick chart, and enriched wealth management products, thus satisfying the all-round wealth management demands of users; Xiaofang launched new version of homepage directly linked with consultation column, wealth management and data center, and supported the risk evaluation of institutional clients; a few APPs like Jintaiyang incurred a comparative drop of active users because the new mobile APP had a division effect on the old version.
In the era of digital assets, the development tendency is to stress product development on mobile terminal. Accordingly, the application of financial technology in the securities service marketwill be increasingly enriched and bring the brand-new user experience and interaction mode.
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 moreaccurate recognition.
2. Data Processing Side: By machine learning algorithm, the data completion algorithm is enabled for fragmented behaviors of the users, the equipment uniqueness identification algorithm is upgraded, filtration algorithm of 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.
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 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. As of the third quarter of 2017, the monitoring results of Analysys are based on cumulative installed coverage of 2.19 billion users and 520 million active users on mobile terminal. Analysys helps you effectively understand the trace of users on mobile terminal by adopting independent enfoTech.