With the explosive growth of the digital economy on a global scale, digital transformation and upgrading have become a consensus for development. As the main battlefield and benchmark for innovative applications of cutting-edge technologies such as big data and artificial intelligence, the banking industry has put forward higher requirements for the independent and stable use of big data and AI technology, and the amplification of technological dividends.

The banking industry is accelerating the construction of more flexible, efficient, and autonomous AI capabilities and real-time data processing capabilities, in order to accumulate AI assets and accelerate the process of enterprise level intelligent transformation and upgrading. At the same time, the banking industry also faces many challenges, such as controlling and mitigating various risks under the three principles of liquidity, safety, and profitability to ensure stable operations; Strictly control the deposit loan ratio and interest rate pricing of customers to ensure a stable source of profit; Facing massive customer and transaction data, relying on new technological means to meet the diverse needs of customers, in order to obtain potential business opportunities and maintain excellent customer satisfaction.