On the afternoon of April 24, Yu Xiaoning，the Ph.D. of Brunel University, also the general manager of Nanjing Sairong Information Technology Co.,Ltd., gave us a presentation in Weiyu 117 entitled " Risk management of commercial banks based on the analysis of financial data ". At the same time, the executive vice president Sun Yang and Dr. Yu Xiaoning attended the signing ceremony. Teachers and some students from the institute of economic and financial attended lectures and discussions.
Dr. Sun Yang first introduced Dr. Yu Xiaoning and proposed the use of EAST reports in the banking industry as background information. Dr. Yu then introduced the company and focused on the products they designed for the bank. Banks make profits through risk management. What they are doing is to provide the results that banks and regulators required by using the big data.
First, the company's main job is data processing. There are three levels of data processing: reports, data visualization, and in-depth data mining. Dr Yu believed that the data processing of finance is similar to technology in the army. It is about how to model ambiguous events to make it visible. He also introduced the practical application of mobile cockpit designed by the company.
Secondly, Dr. Yu introduced the three characteristics of Sai Rong’s products.
Firstly, data analysis is based on data warehouse technology. The data warehouse is different from the database. In the database, the data is saved in the minimum space and redundancy is not allowed. The most important thing in the era of big data is that we can search the data that we required as quickly as possible. This is why the data warehouse appears. With the data warehouse, the bank can drill through the data to see the result in the units of second.
The second characteristic is self-inspection and monitoring using more than 500 risk models. The bank's 1104 and EAST data, including all of the bank's trading data, requires many resources to collect, but are not fully used. The Banks need the data to provide guidance for themselves, and the CBRC needs the data to make it easier for monitoring. According to the CBRC's requirements, the CBRC has made more than 500 models for automatic inspection, making it easier for decision makers to make decisions, and also facilitating the supervision of regulators.
Third, the application of artificial intelligence in banking. There are many models in artificial intelligence, which are already very mature. The key question is how to apply it. In banking, fraud and anti-fraud are of great importance. Until now, the rules of the model have been written, but the fraudsters have the opportunity to continue to cheat through the oversight of the rules. Setting the rules automatically by machine learning is the future. In the end, Dr. Yu also discussed the specific application of cluster analysis in products.
After the meeting, the teacher of the institute discussed the theoretical basis of machine learning with Dr. Yu.
