**["Token Loans" Roll Out Successively: How Computational Power Data Becomes a Credit Asset]** As the fundamental unit for processing information in artificial intelligence (AI) large models, tokens are rapidly entering financial service scenarios, with some banks using them as one of the reference indicators for credit evaluation. Recently, several banks have launched "Token Loan" products, opening up new financing opportunities for asset-light, tech-driven enterprises that lack traditional collateral. **Token Consumption Incorporated into Credit Evaluation Indicators** Recently, Wenzhou Jinku Network Technology Co., Ltd. secured a loan of 200,000 yuan from the Agricultural Bank of China based on its historical token settlement data, computational power procurement contracts, downstream business orders, and independent intellectual property. The funds were earmarked for computational power procurement to meet the company's working capital needs. Amid the wave of the digital economy, computational power has become a core production factor for AI enterprises, and token consumption has been rapidly climbing. According to data from the National Data Bureau, the average daily token call volume in China surpassed 140 quadrillion in March, over 1,000 times the volume two years ago. Behind the surging demand for computational power, the financing challenges faced by AI enterprises are becoming increasingly prominent. Over the past two years, many banks have tailored financing products like "Token Loans" for AI enterprises, incorporating data such as token consumption, computational power service contracts, and business orders into credit evaluation indicators. This approach breaks away from the traditional credit risk management reliance on physical collateral like factories and equipment. Several interviewed banks emphasized that it is not a simple equation of "the more tokens used, the more you can borrow." Instead, they conduct multi-dimensional cross-verification using data such as computational power contracts and accounts receivable, and comprehensively determine the credit limit based on the enterprise's operations, financials, and credit history. (Source: Xinhua News Agency)