11月21日，北京金融监管局网站发布批复，核准丁国祥东风汽车金融有限公司董事长的任职资格。公司 应要求上述核准任职资格人员严格遵守金融监管总局有关监管规定，自本行政许可决定作出之日起3个 月内到任，并按要求及时报告到任情况。未在上述规定期限内到任的，本批复文件失效，由决定机关办 理行政许可注销手续。 ...

（原标题：央行北京分行等12部门，最新发布！） 二、加大重点领域金融支持，挖掘消费潜力 （一）加大商品消费信贷支持力度。积极开展汽车贷款业务，合理确定贷款发放比例、期限和利率，适 当减免汽车以旧换新过程中提前结清贷款产生的违约金。引导金融机构针对首次购买、以旧换新、二手 车等不同购车场景优化创新金融产品，加大对汽车特别是新能源汽车消费的金融支持力度。鼓励金融机 构积极满足家电以旧换新、绿色智能家居家装、电子产品等领域消费金融需求，通过多种形式参与商家 促消费活动，提供消费贷款、信用卡分期费率优惠等活动，为消费者适当减费让利。 （二）促进文旅体育消费提质升级。依托首都作为全国文化中心和国际交往中心的功能定位，深挖历史 文化特色资源，围绕全民阅读、文艺演出、直播探店、非遗传承、乡村文旅、民俗文创等领域和北京消 费季"京彩四季"主题活动，创新融资模式，加大信贷投放力度。更好发挥东城区国家文化与金融合作示 范区的引领示范作用，提升辖内银行文化金融服务能力。充分发挥首都"双奥之城"优势，鼓励金融机构 围绕"赛事+"、冰雪经济等消费场景丰富金融产品，探索开展"门票收益权质押"等融资模式，着力培育 精品赛事体系和赛事运营企 ...

Core Viewpoint - The People's Bank of China and 12 other departments have issued a plan to enhance and expand consumption in Beijing through financial support measures, focusing on bond market financing and consumer credit expansion [1] Group 1: Financial Support Measures - The plan emphasizes increasing financing support in the bond market for eligible enterprises in cultural, tourism, and education sectors [1] - It encourages qualified technology innovation enterprises to raise funds through the bond market to enhance the quality of smart elderly care and smart medical products [1] - Financial debt issuance is supported for eligible consumer finance companies, auto finance companies, and financial leasing companies to broaden funding sources and expand consumer credit [1] Group 2: Consumer Credit Expansion - The initiative promotes the securitization of retail loans, including personal auto loans, consumer loans, and credit card loans, to increase the supply capacity of consumer credit [1] - The goal is to activate existing credit stock and enhance the overall consumer credit environment [1]

作者：李凤文 总之，银行下场卖房是特殊时期的战术性选择，核心目标是快速化解风险、回笼资金，但也需要重视防 范交易纠纷等声誉风险。从长远来看，构建多层次、专业化、市场化的不良资产处置体系才是根本之 道。银行应立足金融主业，当好资金提供者与协调者，通过与AMC、科技公司、地方政府的深度协 作，运用更多创新模式化解房地产不良资产风险，既守住金融安全底线，又为房地产市场平稳健康发展 注入持久动力。 责任编辑：王馨茹 但潜在挑战同样不容忽视。银行的核心竞争力在于金融服务，下场卖房缺乏专业销售团队、市场推广经 验和客户资源，可能面临"水土不服"和成本收益失衡的问题。就房产如何做到合理评估、公平定价，有 效防范内部人员以权谋私等，对银行内控管理提出更高要求。同时，出售房产如果在产权、物业费缴纳 等方面存在瑕疵，一旦出现交易纠纷，将直接损害银行声誉。对市场而言，集中入市的低价房源可能短 期压制周边房价，如兰州某"直供房"集中小区，周边二手房成交均价较上半年下跌4.2%，部分业主被迫 下调挂牌价。不过这种影响边界清晰，因"银行直供房"成交量占全国二手房交易总量不足1%，且多集 中在三四线城市或近郊，难以撼动整体房价体系。 值得 ...

值得注意的是，这一现象并非银行独有，消费金融公司、汽车金融公司等非银机构也在加大个贷不良资 产出清力度，共同印证了行业处置模式的转型。 银行下场卖房这一处置方式的利弊呈现多面性。对银行而言，直接卖房能显著提升资产处置效率，加速 资金回笼。同时通过自主把控交易流程，减少信息不对称带来的法律纠纷，最大限度保全资产价值。对 购房者来说，"直供房"成交价普遍低于市场价16%—31%，且交易流程规范透明，还能享受按揭贷款等 配套金融服务，有效解决了法拍房需全款支付的痛点，降低了"踩坑"风险。对市场而言，不良资产的有 序消化避免了恐慌性抛售对房价的冲击，为房地产市场健康发展筑牢缓冲垫。 "银行也在卖房了，比市场价低不少。"近期，兰州、广东等地银行通过线上平台直接挂牌"直供房"的消 息引发市场热议。这些房源凭借显著的价格优势和清晰的产权属性，成为刚需购房者的"捡漏"新选择。 而这背后，是金融机构不良资产处置从"被动清收"向"主动管理"转型的深刻变革。 银行"下场卖房"是特定经济环境下的选择。近年来，受经济下行压力与房地产市场深度调整影响，个人 按揭贷款断供、房地产开发贷款违约现象增多，银行持有的"法拍房""抵债资产"规模持 ...

Core Viewpoint - Banks are actively selling properties at prices significantly lower than market rates, driven by the need to manage non-performing assets and respond to economic pressures in the real estate market [1][2]. Group 1: Market Context - Recent economic downturns and deep adjustments in the real estate market have led to increased defaults on personal mortgage loans and real estate development loans, resulting in a growing scale of "foreclosure properties" and "debt settlement assets" held by banks [1]. - Traditional disposal channels for these assets have faced bottlenecks, with high rates of unsold foreclosure properties due to issues like unclear tax obligations and difficulties in clearing properties [1][3]. Group 2: Benefits of Direct Property Sales - Direct property sales by banks can significantly enhance asset disposal efficiency and accelerate capital recovery, while also reducing legal disputes through better control of the transaction process [2]. - Buyers benefit from "direct supply properties" that are generally priced 16% to 31% lower than market rates, with transparent transaction processes and access to mortgage services, addressing the challenges of full cash payments for foreclosure properties [2]. Group 3: Challenges and Risks - Banks may face challenges due to a lack of professional sales teams and market promotion experience, which could lead to inefficiencies and imbalances in cost and revenue [3]. - Potential issues with property rights and payment of property fees could result in disputes that harm the bank's reputation [3]. - The influx of low-priced properties into the market could temporarily suppress surrounding property prices, as seen in certain areas where average transaction prices have dropped [3]. Group 4: Alternative Asset Disposal Strategies - Besides direct sales, banks can utilize more mature and innovative methods for disposing of non-performing assets, such as packaging them for asset management companies (AMCs) that specialize in efficient asset disposal [4]. - Establishing "special asset divisions" or using asset securitization to attract capital market investors are also viable strategies for risk sharing and maximizing returns [4]. - For properties that are difficult to sell, converting them into long-term rental apartments or affordable rental housing aligns with policy directions and helps activate assets [4]. Group 5: Long-term Strategy - The decision for banks to sell properties directly is a tactical choice aimed at quickly mitigating risks and recovering funds, but it is essential to focus on preventing transaction disputes and reputation risks [4]. - A long-term solution involves building a multi-layered, professional, and market-oriented system for disposing of non-performing assets, with banks acting as financial providers and coordinators through collaboration with AMCs, technology companies, and local governments [4].

Market Overview - The U.S. stock market experienced mixed results, with major indices showing varied performance amid concerns that the Federal Reserve may not lower interest rates in the upcoming meeting [1] - The Dow Jones Industrial Average fell by 309.74 points, a decrease of 0.65%, closing at 47,147.48 points; the Nasdaq rose by 30.23 points, an increase of 0.13%, closing at 22,900.59 points; the S&P 500 dropped by 3.38 points, a decrease of 0.05%, closing at 6,734.11 points [1] Oil Market - Oil prices surged over 2% due to supply concerns following a drone attack on a key Russian energy hub, halting oil exports from Novorossiysk [2] - West Texas Intermediate (WTI) crude oil for December delivery rose by $1.40, or 2.39%, to $60.09 per barrel; Brent crude settled at $64.39 per barrel, up $1.38, or 2.19% [2] Cryptocurrency Market - Bitcoin plummeted over 5%, falling below $95,000; Ethereum also declined by over 3.8%, trading at $3,108.93 [3] Precious Metals - Spot gold fell by 2.06% to $4,085.37, despite a weekly increase of 1.98%; COMEX gold futures dropped by 2.70% to $4,081.00 per ounce, with a weekly gain of 1.75% [4] - Spot silver increased by 4.65% to $50.5723 per ounce, while COMEX silver futures rose by 4.73% to $50.420 per ounce [4] Economic Data - The U.S. Census Bureau plans to release delayed economic data next week, including construction spending, factory orders, and international trade figures [5] - The Federal Reserve's Logan indicated difficulty in supporting a rate cut in December unless compelling evidence of declining inflation is presented [5] Automotive Industry - The number of Americans defaulting on auto loans has reached a record high, raising concerns about the stability of subprime auto lenders following the recent failures of Tricolor Holdings and PrimaLend Capital Partners [8] - Investors are demanding approximately 50 basis points more in yield for the lowest-rated portions of subprime auto asset-backed securities (ABS), pushing the average risk premium to about 170 basis points, the highest since May [8] Company News - Google plans to invest $40 billion in three new data centers in Texas by 2027, which is expected to create thousands of jobs and provide training for students and apprentices [9] - Citigroup raised the target price for Bilibili (BILI.US) from $25 to $27, while Morgan Stanley increased the target price for Nvidia (NVDA.US) from $210 to $220 [10]

随着持续的通胀压力和学生贷款账单的恢复，数百万车主正在努力负担他们的月供。这是在美联储考虑 未来降息路径之际，美国经济出现疲软的最新迹象。 新华财经北京11月12日电惠誉数据显示，越来越多的美国人拖欠车贷。10月，次级借款人至少逾期60天 未付汽车贷款的比例升至6.65%，创下自1994年有记录以来的最高水平。 （文章来源：新华财经） 根据TransUnion的数据，今年风险最高信用类别中的消费者份额有所增加，达到自2019年以来的未见水 平。次级借款人在第三季度占被追踪消费者的14.4%，高于去年同期的13.9%。对于许多借款人来说， 找到一份稳定的工作变得越来越难，经济指标显示9月招聘迟缓，工人需求放缓。包括星巴克公司、塔 吉特百货和亚马逊公司在内的公司最近都宣布了裁员，而一份报告显示，截至10月，今年美国的裁员总 数接近100万，创下自2020年以来同期最高纪录。 ...

Group 1 - The core viewpoint of the article is the launch of XinMM-AM1, the first Agentic AI model in the automotive finance industry by Yixin Group, which aims to enhance customer acquisition, risk control, and operational efficiency, potentially driving the industry into the next decade [1][2] - XinMM-AM1 has approximately 30 billion parameters, with a response latency of less than 200ms and a single card throughput of up to 370 tokens/s, facilitating low-cost large-scale deployment and business services [1] - The model serves as the "core brain" and orchestrator for automotive finance, enabling full-channel interaction, multi-modal perception, global collaboration, and comprehensive security compliance, thus automating decision-making processes [1] Group 2 - Yixin Group is an AI-driven fintech platform that became the first company in China's automotive finance sector to file a generative AI model in 2024 and has implemented large-scale AI applications across all business scenarios [2] - With the launch of the Agentic model, Yixin aims to accelerate AI empowerment in the industry and continue building a smart automotive finance ecosystem [2]

Core Insights - Yixin (02858) officially launched the automotive finance industry's first Agentic large model, XinMM-AM1, at the 2025 World Internet Conference, which is expected to drive the automotive finance sector into the next decade [1] Group 1: Model Specifications - The XinMM-AM1 model has approximately 30 billion parameters, with a response latency of less than 200ms, supporting real-time interaction with voice agents and achieving a throughput of 370 tokens/s per card, facilitating low-cost large-scale deployment [2] - The model is trained on over 15 trillion tokens of data, primarily sourced from Yixin's diverse and rich business scenarios, providing high representativeness and proprietary value [2] Group 2: Functional Capabilities - XinMM-AM1 serves as the "core brain" and dispatcher for the business, enabling full-channel interaction, multi-modal perception, global collaboration, and comprehensive security compliance, thus empowering the entire automotive finance business chain from customer acquisition to intelligent risk control [2] - The model significantly enhances risk control capabilities and business quality while improving the financing application approval rate, addressing the industry's challenges of long cycles, multiple interaction steps, and complex decision factors [2] Group 3: Company Positioning and Future Plans - Yixin is an AI-driven fintech platform with over 2 billion yuan invested in research and development [2] - In 2024, Yixin will become the first company in China's automotive finance sector to file for a generative AI large model, leading the large-scale application of AI across all business scenarios [2] - The launch of the Agentic large model will accelerate AI empowerment in the industry and continue to promote the construction of an intelligent automotive finance ecosystem [2]