“十四五”规划纲要提出，要健全具有高度适应性、竞争力、普惠性的现代金融体系，有序推进金融创新，稳妥发展金融科技，加快金融机构数字化转型，这标志着金融领域的科技创新与数字化建设将迈入多领域、深层次探索与实践的新阶段。
1
促进金融数字化转型
推动产业智能化发展
随着各行业数字化转型的深入开展，金融机构的数字化转型也如火如荼。由于其行业特点，传统金融存在获客难度低、业务增量低、信息不对称、成本高、缺乏差异化服务等痛点，在竞争激烈的市场环境下，无法及时有效响应客户的金融投资需求，提升客户满意度。
[En]
With the in-depth development of digital transformation in various industries, the digital transformation of financial institutions is also in full swing. Because of its industry characteristics, traditional finance has the pain points of low difficulty in obtaining customers, low incremental business, information asymmetry, high cost and lack of differentiated services, in a highly competitive market environment, unable to timely and effectively respond to customers’ financial investment needs and improve customer satisfaction.
从制造到零售，从教育到医疗，基于大数据的人工智能在过去十年里得到了很大的发展，积累了大量的技术、分析方法和应用案例。金融市场数据的复杂性和大数据分析的便利性使人工智能能够迅速渗透到金融行业，专注于产品设计、营销、风控、客户服务和支持活动的核心需求。在收购增量业务、降低风险成本、优化运营成本、提高用户满意度等方面提升其应用价值，逐步朝着提供差异化服务和积极引导投资的方向发展。
[En]
From manufacturing to retail, from education to medical treatment, artificial intelligence based on big data has been greatly developed in the past ten years, and a large number of technologies, analysis methods and application cases have been accumulated. The complexity of financial market data and the convenience of big data’s analysis enable artificial intelligence to infiltrate rapidly in the financial industry, focusing on the core needs of product design, marketing, risk control, customer service and supportive activities. in the acquisition of incremental business, reduce risk costs, optimize operating costs, improve user satisfaction and other aspects of its application value And gradually develop in the direction of providing differentiated services and actively guiding investment.
▲智慧金融业务场景全景图
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AI加速渗透金融领域
支撑智慧金融高效落地
人工智能技术已广泛应用于主要的金融应用场景。对于一些重复性的人工劳动，如信息录入、审核、提交等，可以用数字化的业务流程来替代人工智能技术的赋能，以降低人力成本。同时，将人工智能与金融业务场景深度融合，利用知识图谱构建产业链全方位知识架构，实现数据的有效积累和沉淀，在一定程度上打破了数据孤岛的窘境。探索利用独立数据价值，构建面向千家万户客户的普惠金融，如量化投顾、智能投顾等典型应用，提升线上线下服务范围和效率。提供定制化服务和投资解决方案，赋能数字普惠新发展模式。
[En]
Artificial intelligence technology has been widely used in the main financial application scenarios. For some repetitive human work, such as information input, check, submission and so on, the enabling of artificial intelligence technology can be replaced by digital business processes to reduce labor costs. At the same time, artificial intelligence and financial business scenarios are deeply integrated, and the knowledge graph is used to build an omni-directional knowledge architecture of the industrial chain to realize the effective accumulation and precipitation of data, which breaks the dilemma of data isolated island to a certain extent. Explore and make use of the value of independent data to build inclusive finance for thousands of customers, such as quantitative investment, intelligent patronage and other typical applications to improve the scope and efficiency of online and offline services. Provide customized services and investment solutions to enable the new development model of digital inclusion.
应用机器学习算法，可迅速掌握海量金融大数据中的各种规律及方法，从而在金融业务的各个阶段有效地优化流程、提升效率。随着金融线上业务的深入开展，账户验证、支付确认等应用场景均需要用户进行远程的身份核验，涉及到物体检测、图像分析、人体姿态识别等技术，通过对验证对象的识别分析，使计算机高效智慧地替代肉眼识别。在其他如证件识别、票据识别等对应场景下，通过图像检测、图像分类、光学字符识别（OCR）、同步定位与建图（SLAM）等细分领域技术，取代重复的人力操作，极大程度地降低了业务成本且提升了效率及准确率。
金融业作为RPA的主流应用领域之一，无论是被动客服咨询的虚拟数字人，抑或主动引导投资的智慧算法模型，相较人工，更具有便利性及针对性，文件报送、税款核算、风险监控等功能就在我们身边。此外，随着科技发展的日新月异，更多人工智能的细化领域如脑机接口、多模态分析等技术也将持续突破，这也对底层算力提出了更高要求。
Original: https://blog.51cto.com/u_13835362/5548528
Author: 坤前服务器
Title: AI+金融驱动金融信创“芯”生态
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