Specific Customer Group Identification System
To enhance service efficiency for high-net-worth clients, the bank required a solution that could quickly identify valuable customers upon their arrival at the branch.
This internal project was developed to support that goal by integrating video data processing with the bank’s customer management system. The system allows external camera devices to transfer captured video files to the internal OCR (Optical Character Recognition) engine, which analyzes the footage to extract key customer features. These features are then matched against the existing customer database using unique identification codes.
When a high-value customer is successfully identified, the system automatically notifies the branch hall manager, enabling staff to deliver personalized and timely services.
Although the application itself is not very complex, it is a completely new project, so I had to set up everything by myself — both the frontend and backend.
System Architecture
Personal Contribution
During my involvement in the New ATMC project, I was responsible for the following:
Frontend & Backend System Setup
- Built the foundational frontend and backend systems to support the migration from the NCR Platform.
User Authentication
- Implemented user login functionality for secure access to the system.
Key Customer Registration
- Developed the registration process for important clients, ensuring data integrity and security.
Automated Organization Data Import
- Created a scheduled import feature to regularly update organization information from external sources.
Documentation
- Authored API documentation for developers and test documentation for QA validation.
