No abstract

With the rapid development of computer network technology, the concept of “Internet +” has become more and more popular in recent years. The combination of the Internet and finance has particularly attracted people’s attention, and the operating modes of many industries have also changed. Since the use of Internet technology can achieve data sharing and information exchange, the “Internet + Finance” model has broken the barriers of information asymmetry in the financial sector in the past and has made great contributions to China’s multiple improvements. The financial market is very important to China’s economic development. The identification of the ID function of the wireless sensor network is susceptible to interference and the identification accuracy is reduced. We propose an adaptive identification feature recognition algorithm based on an improved minimum gray tree. After calculating the similarity, the nearest neighbor matching algorithm is directly used to obtain the minimum matching cost corresponding to the wireless sensor network registration that is regarded as the recognized identity so as to realize the identity function adaptive recognition. In this regard, the simulation results show that the proposed algorithm has high recognition accuracy. With the pace of financial innovation, financial institutions have achieved rapid development on the basis of Internet service platforms. At the same time, as the core of preventing money laundering activities, financial institutions are also facing many issues in identifying “customers” in their work. This article analyzes the main content, implementation effects, and difficulty of customer identification in financial institutions and proposes relevant improvement plans.