Artificial Intelligence, as a new technical science for the study and development of theories, methods, technologies, and application systems used to simulate, extend and expand human intelligence, has a wide range of applications in the field of electronic payments.
First, Payment user identification application
User identification is the starting point of payment, and the common medium security authentication + password authentication method, with the development of artificial intelligence, has begun to appear in the trend of using biometric identification for replacement. Fingerprint recognition, face recognition, retina recognition, iris recognition, finger vein recognition, palm print recognition, etc., have begun to enter the field of payment, greatly facilitating the user. Further, by collecting features of people's "unconscious" behaviors and behaviors (such as walking gait, typing rhythm, etc.) and "more natural" interaction methods (such as voice interaction and brain-computer combination), we can eventually enable people to complete identification with fewer or even no attached objects. Identity recognition, to achieve the convenience of "human is the carrier", to reach the senseless recognition.
Second, The intelligent payment account application
The accounting system is the basis of the payment business. Through the mapping technology of artificial intelligence, various accounts of users are clustered and correlated to give a user portrait, realizing the separation of transaction accounts and payment accounts from the information platform user system to the trading platform, and then the association of transaction accounts and payment accounts to the trading platform. By binding bank II and III accounts with Internet accounts, it facilitates banks and platform finance to make efforts in customer acquisition, live customers, capital operation, transaction finance, and value creation, and helps banks and platform finance to operate in Internet, scenario-based and platform-based.
Third, Innovative payment scenario application
With the continuous progress of artificial intelligence technology and the integration of new technologies such as the Internet of Things, not only will the traditional payment scenarios such as retail and catering be transformed, but more brand new payment scenarios will be born in the future, such as automobile, home and medical, etc. The new application scenarios need to be matched with new payment solutions, such as home payments, automobile payments, etc., to realize the satisfaction of human demand for transactions anytime and anywhere.
Fourth, Mining payment Big Data applications
Payment as a basic human economic behavior, in the social system, has generated a large amount of basic data but has always existed in isolation from other behavioral data, forming a silo of information. With the advancement of artificial intelligence technology, the first application is based on the intelligent processing of user IDs, forming a single relational database of all kinds of data and establishing a data warehouse, which no longer becomes an independent source of information for each. Based on the formation of the data warehouse, the second application of AI is data mining and knowledge discovery of the data. With the development of artificial intelligence, through intelligent means, the system of data classification, clustering, association rule mining, personalized recommendation, prediction, etc., based on the user's browsing, clicking, collecting, purchasing, and other behavioral data to infer the user's age, gender, purchasing ability, hobbies, etc. can indicate a person's portrait, thus allowing the commercial value of payment data to be highlighted.
Five. Intelligent risk management applications
The rapid development of artificial intelligence technology has enabled the payment industry to form an analysis and decision-making mechanism based on big data, "Internet + big data + artificial intelligence + financial risk control" is the main form of future payment risk control. The application of artificial intelligence models such as neural networks, expert systems, support vector machines, and hybrid intelligence in the field of payment risk management can improve the speed of data processing, deepen the depth of data analysis, and reduce labor costs, thereby improving the effectiveness of financial risk control.
Sixth, Intelligent customer service applications
The payment industry directly serves the C-sides, and the perfect customer service support system is the top priority of the payment industry. With the continuous development of artificial intelligence technology, intelligent voice service, intelligent voice quality inspection, intelligent robots, and intelligent knowledge bases have played a special role. Using intelligent voice recognition and analysis technology, on the basis of traditional IVR, the intelligent, humanized and highly efficient "intelligent voice service system" is built in real-time through voice recognition and analysis technology to realize "flat management" of IVR menu, quickly meet Customer demand and customer satisfaction. Based on voice analysis technology, the intelligent voice quality inspection and analysis system provides automated quality inspection functions, listens to users' voices, and digs up voice values. Intelligent robots perform intelligent intent recognition of user questions from various electronic channels, realize knowledge queries and various business processes by docking the knowledge base according to the recognition results, and finally return the results to the channel terminal in a reasonable and customizable way to show to users.
Seven. Blockchain Application
Financial institutions and Internet platforms, with billions of users and more accounts waiting to be verified every day, require a higher degree of automation. At the same time, the proof of qualification to prove the identity is also a variety of names, the authenticity is difficult to distinguish. Artificial intelligence + blockchain technology can achieve safe and reliable management of digital identity information, enhance the efficiency of customer identification and reduce costs while ensuring customer privacy. Through programmed recording, storage, transmission, verification, and analysis of information data, a large number of labor costs and intermediary costs can be eliminated, accuracy and security can be improved, and the recorded credit information is more complete and difficult to falsify.
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