In recent years, from the top-level strategy to the implementation of applications, the value contained in big data has undoubtedly become a fact, and data mining technology and applications have also become hot spots for discussion and pursuit in all walks of life. The banking industry has a natural data advantage and the basis of informatization. At the level of data, it also has first-mover advantages and genes. Data is the oil in the era of big data and the core asset of the financial industry. It has become a consensus in the industry. Based on this, Bank of China Jiangsu Branch launched a strategic plan to train a group of compound talents who understand business, tools and data.

In this June of Jinxia , CDA Data Analysis Institute was invited by the Bank of China Jiangsu Branch to bring a 4-day data mining talent sharing meeting to it. It ended successfully at Nanjing Information Management College. Expert Li, who has rich experience in financial data mining The teacher and teacher Ding gave systematic explanations from different aspects such as strategy, thinking, knowledge map, practical cases, software applications, etc. More than 50 on- site participants came from the financial management department, risk management department, operation management department and information technology department of the provincial bank , Bank Card Department, Personal Finance Department, Internet Finance Department, Channel Management Department, Wealth Management and Private Banking Department, Corporate Finance Department, SME Department, Internal Control and Legal Compliance Department and Dogo branch selected excellent employees together , Study and discuss the big data thinking mode together, and the four-day sharing has won unanimous praise from the students.

The sharing also inspired the students to think a lot, and the students also released a lot of work ideas and knowledge that they want to improve and learn in the future . For example, to explore the potential of customers both inside and outside the airline through inventory customer analysis to enhance financial assets and contribution; use data analysis to improve the effectiveness of market fees; intelligent counter risk early warning analysis; personal customer product purchase intention calculation; analysis of private deposit loss; the causes of bad credit for SMEs Quantitative analysis; application of failure rate risk warning and other very valuable thinking exploration and mining application attempts.

Next, the CDA Data Analysis Institute will work more closely with BOC to help BOC improve the strategic layout of the three-dimensional financial talent training, and continue to write the story of data and data people.