As the basic unit for processing information in the big model of artificial intelligence, the word element is rapidly entering the financial service scene, and some banks use it as one of the reference indicators for credit granting. Recently, many banks' “Token Loan” products have been launched one after another, opening up new financing space for asset-light science and innovation enterprises that lack traditional collateral. Token consumption was included in the credit reference index. Recently, Wenzhou Jinku Network Technology Co., Ltd. obtained a loan of 200,000 yuan from the Agricultural Bank based on historical term settlement data, computing power procurement contracts, downstream business orders, and independent intellectual property rights. The funds were targeted for computing power procurement to meet the capital turnover needs of enterprises. Under the wave of the digital economy, computing power has become a core production factor for AI companies, and token consumption is rising rapidly. According to data from the National Data Bureau, the average number of daily token calls in China exceeded 140 trillion dollars in March, more than 1,000 times that of two years ago. Behind the strong demand for computing power, the financing problems of AI companies are becoming more and more prominent. In the past two years, many banks have tailored financing products such as “Token Loans” for AI companies, incorporating data such as token consumption, computing power service contracts, and business orders into credit indicators, breaking through the risk control inertia of traditional credit that relies on physical collateral such as factories and equipment. A number of banks interviewed said that instead of “how many tokens you use, how much money can you borrow”, they also need to combine multi-dimensional cross-verification of data such as computing power contracts and accounts receivable, and comprehensively approve credit lines based on the company's operating, financial, and credit information conditions.

As the basic unit for processing information in the big model of artificial intelligence, the word element is rapidly entering the financial service scene, and some banks use it as one of the reference indicators for credit granting. Recently, many banks' “Token Loan” products have been launched one after another, opening up new financing space for asset-light science and innovation enterprises that lack traditional collateral. Token consumption was included in the credit reference index. Recently, Wenzhou Jinku Network Technology Co., Ltd. obtained a loan of 200,000 yuan from the Agricultural Bank based on historical term settlement data, computing power procurement contracts, downstream business orders, and independent intellectual property rights. The funds were targeted for computing power procurement to meet the capital turnover needs of enterprises. Under the wave of the digital economy, computing power has become a core production factor for AI companies, and token consumption is rising rapidly. According to data from the National Data Bureau, the average number of daily token calls in China exceeded 140 trillion dollars in March, more than 1,000 times that of two years ago. Behind the strong demand for computing power, the financing problems of AI companies are becoming more and more prominent. In the past two years, many banks have tailored financing products such as “Token Loans” for AI companies, incorporating data such as token consumption, computing power service contracts, and business orders into credit indicators, breaking through the risk control inertia of traditional credit that relies on physical collateral such as factories and equipment. A number of banks interviewed said that instead of “how many tokens you use, how much money can you borrow”, they also need to combine multi-dimensional cross-verification of data such as computing power contracts and accounts receivable, and comprehensively approve credit lines based on the company's operating, financial, and credit information conditions.