Investment decision-making, risk management and other scenarios, reshaping the traditional financial services and other aspects have applications.

With the widespread popularity and mature development of big data technology, the application of financial big data has become a hot trend in the industry, in transaction fraud identification, precision marketing, blackmail prevention, consumer credit, credit risk assessment.

Supply chain finance, stock market quote prediction, stock price prediction, intelligent investment adviser, fraudulent insurance identification, risk pricing and other specific business involving multiple fields such as banking, securities, insurance, etc., has been widely used. The ability to apply and analyze big data is becoming a core competitive element in the future development of financial institutions.

Stock market forecast:

Big data can effectively broaden the dimension of quantitative investment data for securities companies, and help them to understand the market situation more accurately. With the widespread application of big data, explosive growth in data size and significant improvement in data analysis and processing capabilities, quantitative investment will have access to a broader range of data resources, to build a more diverse range of quantitative factors, and a more complete investment research model.

Securities companies apply big data to the massive individual investor samples for continuous tracking and monitoring, and a series of indicators such as book investment returns, position rates, and capital flows are statistically and weighted summarized.

To understand the changes in trading behavior of individual investors, the state and development trend of investment confidence, the expectations of the market and the current risk appetite, etc., to predict the market situation.