5. Opportunities, Risks, and Breakdowns Brought by AI to Commercial Banks

Since the coining of the term “Artificial Intelligence” (AI), its definition scope has evolved from an application program with pre-set rules of logic, to a technology that simulates human cognitive function. The goal of AI is to allow computers to imitate human intelligence, perception, thinking, and action, so as to achieve automation and gain analytical insights. To imitate human intelligence, AI applications adopt two methods: rule-based and non-rule-based algorithms. Rule-based AI uses pre-set rules to “learn”, while non-rule-based AI uses machine learning algorithms to “learn” and a trained AI model to “think”. The key driving force for the development of AI is the huge increase of available data and the great improvement of computing power in traditional computers and mobile devices, as well as the continuous development of machine learning algorithms. Commercial banks conduct large numbers of customer capital transactions, and hold large amounts of account management information. The application of AI in commercial banks will effectively improve the retail service level, enhance customer experience, and alleviate difficulties such as “financial disintermediation” and fierce market competition, or become the next profit growth point of commercial banks.