First, the data must be secure. The so-called security is that the data generated by the bank itself is to protect the rights and interests of users are not infringed upon, and will not be used for other purposes. Secondly, be careful about using external data. Currently on the market, some of the so-called big data wind control company in the data acquisition and use of loopholes in the regulations, heavily polluted data will only bring greater obstacles to the development of business, need to be cautious. Compliance with legal data sources is a way to control their own risk.

Again, a more basic and in-depth study of the data. Some game companies are better at mining user behavioral data, and from this there is also very much the counterpart of game psychology to conduct research. Although, there is a big difference between financial data and gaming data, gaming companies do have their own unique characteristics in terms of player privacy protection and player needs mining, which is very worthwhile for banks to figure out.

Finally, be ready before the credit market is perfected and the era of IoT finance arrives. In the era of IoT finance, the amount of data will be even larger, and if the data is false to begin with, the value of cleaning and utilizing it will amount to zero, and could even take digital transformation off the runway.

For financial institutions, data integration and business intelligence are still mostly led by the big data team, but realizing the value of data needs company-wide attention, starting with the leadership

Summary; data-based transformation is a very important task. In the traditional financial industry, there is a common problem of "decision making", but once the data culture is established, it can better control these problems, such as the leadership in the sense of making decisions, employees can use data to convince the boss to make more scientific decisions.