Credit Fraud Detection @ING BANK

About

ING Bank approached Samsung for help in preventing fraudulent credit applications. Samsung was familiar with our face recognition algorithm work and referred us for this project.

The fraudulent individuals repeatedly applied for credit with fake identities by changing their physical characteristics. At the start of the project, we first extracted face maps of individuals on the bank's blacklist. The developed algorithm then examined credit applications made through the internet or branch environment. The application would alert relevant staff in case of possible similarities.

My role in the project was to write the face recognition and matching algorithm according to customer needs and to serve as the team leader for developing the application interface. I led the development of the user interface for the application that was used to detect fraudulent credit applications.

The solution we offered was a face recognition-based system that helped ING Bank to reduce the rate of fraudulent credit applications. The plan worked by comparing the information provided in a credit application with the existing records of blacklisted individuals and alerting the bank's employees in case of any suspicious activities.

The project was a success, resulting in a significant reduction in fraudulent credit applications. The implementation of our solution was well-received by the ING Bank and its employees, and it effectively improved their overall security measures. This project highlights my expertise in developing advanced solutions in the field of facial recognition technology. It also showcases my ability to lead a team and work with clients to fulfill their requirements and deliver a successful outcome.