Biometric Grid Systems in University Financial Management: Driving Digital Transformation to Support Biotechnology Innovation

Abstract

This study explores the integration of biometric grid systems for the digital transformation of university financial management, emphasizing its role in supporting biotechnology innovation and education. A digital management system leveraging multi-biometric fusion identification technology was designed to enhance security and efficiency in financial processes. The system utilizes an advanced grid cognitive model of biometric identification, with comprehensive testing conducted across four core functional modules: user registration and login, user roles and permissions, face recognition, and data processing. Performance analysis was also performed to evaluate accuracy and response time. Results demonstrate that the system achieves an Equal Error Rate (ERR) of 0.027 on the test dataset, indicating high recognition accuracy. The rounding operation in the scheme has negligible impact on recognition performance. Additionally, under concurrent logins of up to 5000 users, the system maintains a low response time with a login success rate of 99.92%, significantly enhancing the user authentication experience. These functional and performance outcomes highlight the system’s reliability and efficiency in managing complex financial processes. By integrating biometric grid technology into financial management, this research supports the scalability and sustainability of biotechnology education infrastructure. The proposed system ensures secure and streamlined financial operations, enabling universities to allocate resources efficiently and foster innovation in biotechnology programs. This study provides a practical framework for implementing advanced digital systems in academic settings, contributing to the broader goals of optimizing financial management and supporting commercialization efforts in biotechnology.