文/瑞财经 曾树佳 文件落定，李波正式成为了京东消金的董事长。 10月10日，天津金融监管局发布公告称，核准李波天津京东消费金融有限公司（简称"京东消金"）董事长的任职资格，3个月内到任。 目前，他还同时担任京东未来数字科技有限公司法人及朴道征信董事，拥有多重身份。 今年以来，京东不断加码自身的金融版图。 其中在4月份，京东收购了捷信消金，此后，天津金融监管局批复同意捷信消金，更名为天津京东消费金融有限公司（即"京东消金"）。 京东消金目前由广州晶东贸易有限公司（简称"广州晶东"）、网银在线（北京）商务服务有限公司（简称"网银在线"）、中国对外经济贸易信托、天津银 行，分别持股50%、15%、12%、10%。 这次职位的获批，意味着京东消金，基本完成了新管理层班底的搭建。 此前9月8日，天津金融监管局核准李波、刘晓蒙、张素娟和李芳芳的京东消金董事的任职资格。而在此一周前，京东消金的董事潘朝光、李曙光、董晓东 三人的任职资格，也获得核准。 根据李波的履历，他曾担任中国工商银行湖南省分行副行长；2021年3月加入京东，从金融科技群二级部门企业金融业务部机构负责人起步，逐步接替京 东白条"掌舵人"许凌，成为金融科技 ...

Group 1: AI and Big Data in Finance - The integration of artificial intelligence and big data is reshaping the core operational models of the financial industry, with significant developments in China's fintech sector following the global AI wave initiated by ChatGPT [2] - Major financial institutions like ICBC and China Merchants Bank are leading the application of AI in finance, while Tencent Cloud and Ant Group excel in technology output [2] - Ant Group has developed a leading AI risk control system that supports real-time transactions and compliance for hundreds of millions of users [2] Group 2: Evolution of Credit Risk Assessment - The credit risk evaluation system in banks has evolved from information-based to data-driven and intelligent systems, driven by the deep integration of data and technology [3] - Traditional credit risk assessment relied heavily on customer-provided information and internal data, limiting the use of external data [3] - The rise of digital finance allows financial institutions to access a broader range of external data, enhancing the comprehensiveness of risk assessments [3] Group 3: Innovation in Banking Services - Banks are innovating their service models by integrating online and offline channels, enabling personalized services anytime and anywhere [4] - The application of technologies like Intelligent Process Automation (IPA) has significantly improved operational efficiency, reducing processing times from days to minutes [4] - The focus of banking innovation has shifted from product-centric to ecosystem-centric approaches, integrating business, data, and technology [5] Group 4: Challenges in Inclusive Finance - Financial services for small and micro enterprises face challenges due to high service costs and the inherent risk characteristics of these customer segments [6] - Information asymmetry exacerbates the difficulties in risk identification and control in these segments [6] - Data is recognized as a key production factor in the digital transformation, with its marginal utility increasing as it is reused [6] Group 5: Enhancements in Risk Control Models - Traditional risk control models are limited by the narrow scope of data used, often leading to inadequate risk assessments [7] - By integrating diverse data sources, including user behavior and environmental factors, a more comprehensive risk management system can be developed [7] - The value of data increases with volume and reduced application barriers, enhancing both social and economic value [7] Group 6: AI in Anti-Money Laundering - Ant Group's anti-money laundering system combines AI and graph computing to enhance the identification of complex relationships [9] - The system utilizes heterogeneous graph modeling to depict various entities and their relationships, enabling effective tracking of fund flows [9] - AI plays a crucial role in analyzing suspicious transactions and automating report generation, improving decision-making efficiency [10]