A bank credit card big data platform

Project Background
Based on the big data platform, the bank's credit card direct selling center builds a complete set of intelligent service system by virtue of cutting-edge technologies such as data mining, intelligent search, voice recognition, natural language processing and ML, and carries out unified processing of various business data according to the bank's business iteration and policies and regulations, providing customers with robust technical guarantee and knowledge shield, helping users to quickly solve business problems in use and providing obstacle solutions. According to the bank credit card approval, dispatch, card issuance, approval and other links, make information reports of each business team, reflect each business situation, data processing to generate various indicators, to provide support for the group company's decision-making.

Project Construction
Construction period:
2021.12-2023.12 goes online iteratively in two phases;
Project members:
The project has 28 input members, including 6 senior developers, 17 intermediate developers and 5 primary developers.

Customer Value
Banking is a data-driven industry, and the information process has gone through the stages of business electronization, data centralization, and management model. For the digital transformation of the banking industry, it needs to rely on the big data platform, and the construction and maintenance of the big data platform has also become a key part of the project. Only through suitable preprocessing, model design, analysis mining, can we find the potential rules hidden in it. The application of big data technology can extract potentially useful information from massive, inconsistent, random data. Banks can use this information to improve the service efficiency and management level of financial business, and the core business of banks can also get great benefits from it.

Typical Scene

users: The emergence of Internet finance and third-party payment has caused a serious loss of bank users, and at the same time made banks more unaware of the needs of users. By deploying applications that collect users' behaviors on the bank's official website and APP to form user portraits, banks can better understand the behavior characteristics of specific users on the Internet and shorten the distance between banks and users, thus providing data basis for more refined services.