In the era of big data, the Internet industry occupies an important traffic portal and has natural advantages. Finance can be said to be the primary commercial realization scene for the realization of the Internet industry, and it has become a general trend for Internet companies to lay out financial technologies one after another.

And how does finance use big data nuggets?

We take BAT as an example:

The e-commerce data represented by Alibaba mainly includes sales data, user purchase behavior data, commodity data, customer consultation data, after-sales service data, promotion data, marketing activity data, and overall website operation data. Its advantages are convenient commodity operation, convenient user operation and convenient product operation. Compared with searching big data, it has the characteristics of fewer dimensions and relatively concentrated data.

Social data represented by Tencent has the characteristics of group and relationship, accounting for 90% of the total social users, and the average daily traffic exceeds 65.438+06 billion. The advantage is that the group dynamics can be accurately predicted. The defects of social data lie in certain risks and loopholes, such as easy manipulation, easy falsification of single-dimensional data and low cost.

The characteristics of search data represented by Baidu are high-dimensional and sparse. The data covers demographic attributes, interest concerns, consumption scenarios, permanent locations, credit scores, APP behaviors, etc. With rich dimensions, you can make more accurate user portraits. This feature has some similarities with the data in the financial field. The difficulty of traditional finance lies in the large number of customers, rapid technology upgrade and high cost of risk control.

With big data, you need to have the corresponding data cleaning, processing and computing capabilities to realize the application and business realization of big data.

For example, Baidu uses boosting algorithm to deeply learn unique big data, and through function calculation, summarizes some features of high-dimensional data to reduce dimensions.

In terms of credit reporting, after the superposition of Baidu big data and PBOC credit reporting data, it can increase 13% of customer group risk differentiation. At present, the number of creditable users of Baidu Finance has reached 65.438+0.9 billion, empowering more than 400 financial institutions and serving more than one million times a day.

Using big data to mine, in the final analysis, it is necessary to find a scene suitable for data realization and use data with advanced technologies such as artificial intelligence. In addition to BAT, many traditional financial institutions are also exploring this proposition.

For example, a new financial service "data pledge" based on the characteristics of users' transaction and behavior data has gradually matured, that is, using big data technology, rating and granting credit with real transaction data and behavior data that can be cross-verified in the transaction process, and providing financing services for enterprises on this basis. For example, ICBC uses data technology to mine multi-dimensional information of enterprises, portray corporate credit portraits, accurately tap customers' financing needs, and provide customers with "one-click loan" bank-wide financing services. Welcome to express your different views and communicate with each other in the comments. Thank you!