Abstract
The modern society is undergoing tremendous changes due to technological innovation. The birth of new technologies such as artificial intelligence (AI), Internet of Things (IoT), big data, and cloud computing marks the beginning of the fourth industrial revolution. Various new industries are rapidly emerging as information and communication technology (ICT), artificial intelligence, big data, and other new technologies such as the Internet of Things are combined. Fintech is a technology that is attracting attention as new technologies and the financial industry merge. The concept of Fintech was born through the convergence of financial industry and information and communication technology by governments of all countries around the world and continuous innovation. Fintech is an innovation in the financial industly that uses new technologies. Use aiiificial intelligence, big data, cloud computing, the Internet of Things and other modern science and technology achievements to reform financial products, business models and business procedures. One of the most basic tasks in financial business is payment service. The development and introduction of new technologies has changed the way people pay. One of the notable fields in payment service is face recognition payment. Face recognition is being used in various fields due to its high accuracy and low invasiveness. Facial recognition payment is a technology that uses computer vision. It uses computers to mimic human vision, allowing computers to analyze images. It is a technology that implements identity authentication based on personal facial feature information. The purpose of this study is to analyze the effect relationship of facial recognition payment on usage intention. For basic statistical analysis of the questionnaire, SPSS 23.0, a statistical package, was used. For hypothesis testing, concentrated validity and discriminant validity were verified using the structural equation package Smart PLS 4.0. Infmmation technology factors that dete1mine face recognition payment were divided into system characteristics and user characteristics. A summary of the study follows. First, The system characteristics of the face recognition payment service were partially adopted for user resistance. Second, the user characteristics of face recognition payment had a significant effect on user resistance. Third, user resistance had a significant effect on intention to use.
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