Core Insights - The true value of AI lies not only in its advanced technology but also in its ability to address real-world problems in various industries, as emphasized by Ant Group's CEO Zhao Wenbiao at the Ecological Partner Conference [1] Group 1: AI Implementation and Industry Focus - Ant Group has focused on "technology landing" over the past year, successfully integrating AI into real business scenarios across key sectors such as finance, energy, transportation, and manufacturing, collaborating with nearly 20 leading partners to launch over 100 intelligent joint solutions [4] - The company has strategically targeted the financial sector, which has the highest data thresholds and compliance requirements, becoming the preferred partner for AI transformation in this industry, covering 100% of state-owned joint-stock banks and over 60% of local commercial banks [5] - The collaboration with Ningbo Bank has led to the development of an intelligent decision-making system that significantly improved the accuracy of complex problem responses from 68% to 91%, with response times reduced to milliseconds [5] Group 2: Technological Innovations and Applications - The AI mobile banking application launched by Shanghai Bank, powered by Ant Group's technology, allows users to perform high-frequency transactions through natural language interactions, marking a significant shift in user experience [6] - Ant Group's AI capabilities have extended beyond finance to public services, exemplified by the "Little Blue Whale" intelligent bus system in Nanjing, which has optimized public transport scheduling and improved operational efficiency [7][8] - The EnergyTS model released in March has enabled large-scale applications in the energy sector, enhancing investment decision efficiency by over 60 times and improving operational and trading outcomes by more than 10% [9] Group 3: Comprehensive Technology and Global Expansion - Ant Group has developed a full-stack product matrix focusing on business growth, user experience, and risk management, validated by its performance in global benchmarks [9] - The company has been recognized as a leader in the IDC MarketScape for its comprehensive technology capabilities and deep experience in the financial sector, and it is expanding its AI solutions globally [10] - The "Star Plan" launched by Ant Group aims to enhance partner capabilities across four dimensions, fostering a collaborative ecosystem to drive the large-scale implementation of industrial AI [11][14]

12月10日，艾瑞咨询（iResearch）正式发布《iResearch Vendor Insight：中国金融智能体发展研究与厂商评估报告 (2025)》报告。该报告将蚂蚁数科置于综合 领导者象限，认可其在金融智能体领域的技术引领性与场景落地能力。 当前政策聚焦"科技-产业-金融"循环体系，据预测，2028年金融科技市场规模将突破6500亿元。在此行业背景下，金融智能体已成为机构数智化转型的核心 支撑。艾瑞咨询在报告中提到，蚂蚁数科的核心竞争力源于蚂蚁集团服务十亿级用户的"金融原生"基础——这种将深度金融业务理解与企业级AI工程能力系 统融合的特点，使其在AI原生App、财富管理、信贷风控、智能营销等核心场景中，形成了明显的差异化优势。 艾瑞咨询在报告中预测，2028年底，预计80%的金融机构会采纳至少一种智能体工具。在这个时期，35%以上的金融智能体应用已经形成规模化落地范式， 行业迈入规模扩展期。 财经频道更多独家策划、专家专栏，免费查阅>> 基于这一架构，蚂蚁数科自主研发的金融推理大模型Agentar-Fin-R1（包含32B和8B参数两个版本）成为技术核心。该模型在三项重要金融基准测试中均取 得第一 ...

IDC最新发布的《中国智能体开发平台2025年厂商评估》给出了一个清晰信号：智能体正成为企业AI转 型与流程重构的核心。拥有全栈能力与行业经验的平台厂商已抢占先机，未来竞争将集中于复杂智能体 与应用的一体化开发。 蚂蚁数科旗下的 Agentar 全栈企业级智能体平台，正是在这轮转向中，被IDC评为"领导者"的代表之 一。更关键的是，它率先在金融这个最难落地、也最具价值的行业，跑通了智能体规模化应用的路径。 二、从"能用"到"敢用"， 一、导语 过去一年，智能体几乎成为所有大模型厂商的"标准配置"。代码智能体、办公智能体、营销智能体层出 不穷，但真正进入核心业务系统、能跑在生产一线的属于少数。 金融为什么是智能体的终极考场？ 金融几乎就是智能体的"终极考场"。 一方面，它是对 AI 最渴望的行业之一。从客服、风控到投研、运 营、合规，金融的每一个环节都建立在对信息密度、处理效率和人力规模的极致依赖之上：海量文本、 实时数据、复杂规则、快速决策，天然适合交给智能体来承担。 但与此同时，金融也是对 AI "不够友好"的行业。首先是数据的高度敏感与封闭。金融数据天然带有隐 私属性和机构壁垒，既涉及个人资产、征信、交易 ...

Core Insights - Ant Group and Ningbo Bank's collaboration on the "Agentar Knowledge Engineering KBase" has been recognized as an exemplary case for international financial applications, showcasing its potential to enhance business intelligence in the financial sector [1] - The financial industry faces challenges related to "knowledge silos," where critical information is dispersed across different systems, leading to inefficiencies in service and consultation experiences [1] - The Agentar platform integrates knowledge processing management, logical reasoning engines, and intelligent application scenarios to provide a robust decision-making system for financial institutions [1] Technology and Implementation - The platform manages multi-source heterogeneous data throughout its lifecycle and features capabilities such as intelligent Q&A, knowledge processing, multi-route recall, and knowledge management [2] - A significant technological breakthrough is the knowledge-enhanced generation engine, which utilizes a collaborative mechanism of "planning-retrieval-reasoning" to improve knowledge quality through bidirectional indexing of knowledge graphs and raw text [2] - The system has transitioned from "fuzzy matching" to "precise reasoning," increasing reasoning depth from traditional 1-hop to 3-5 hops, enabling AI to understand financial knowledge and exhibit human-like logical reasoning [2] Performance Metrics - The solution has been implemented across various internal scenarios at Ningbo Bank, including market analysis, product interpretation, dialogue practice, and report writing [2] - Evaluation results indicate that the accuracy of complex Q&A has improved from 68% to 91%, with response times reaching the millisecond level [2] - Content recommendation accuracy has increased by 35%, and recall rates have improved by 40%, leading to a significant enhancement in business efficiency [2] Future Directions - Ant Group and Ningbo Bank plan to deepen their collaboration by expanding the technology to a broader range of financial business scenarios [2] - The partnership aims to actively participate in industry standardization efforts, promoting the regulated and large-scale application of knowledge engineering and large model technologies in the financial sector [2]