The hottest AI changes the landing scenario of fin

  • Detail

AI changes Finance: artificial intelligence landing scenario, leading financial intelligence

[editor's note] technology will become the core driving force for the sustainable development of the financial industry in the future. On the one hand, the new technology represented will bring great benefits to financial institutions, and on the other hand, due to problems such as black boxes, regulators will face greater challenges

development characteristics of artificial intelligence + financial industry: technology providers mainly provide various technical products and solutions for traditional financial institutions through creation, cooperation and empowerment. At present, the development of the industry is still at an early stage, waiting for the continuous development of technology and the continuous integration with the financial scene

future competition pattern of science and technology enterprises: the competition of science and technology enterprises will tend to be mature and rational, and the science and technology giants with technology, capital, talents and scene advantages and the benchmark enterprises in the subdivided fields with technology advantages will achieve long-term development

the future evolution trend of the financial industry: the financial industry will realize real inclusive, on the one hand, making better financial services cover small and micro enterprises and more long tail customers, on the other hand, making the operating costs of financial institutions further reduced, and finally realizing the improvement of the whole social welfare

future development direction of financial supervision: China's financial supervision can learn from some mature foreign experience, establish a special financial technology supervision institution in combination with China's national conditions, strengthen the research and exploration of new technologies, innovate in supervision means, and better respond to the future development and challenges of the industry

Industry Overview: definition of AI + financial industry

AI technology helps the transformation and upgrading of traditional financial business

AI + finance is obviously different from the definition. Financial technology mainly refers to the combination of emerging technologies in a broad sense (big data, cloud computing, blockchain, artificial intelligence) and the financial industry. IResearch believes that AI + finance is mainly driven by AI core technologies (machine learning, knowledge mapping, natural language processing, computer vision) to empower all participants and business links in the financial industry, highlighting the important role of AI technology in product innovation, process reengineering and service upgrading of the financial industry. This report focuses on the characteristics of the artificial intelligence + financial industry defined above, and describes the development status and future prospects of the artificial intelligence + financial industry

the development process of technology application in the financial industry

technological progress promotes the evolution of the financial industry from informatization to intelligence

throughout the development history of the financial industry for more than half a century, every technological upgrading and change relies on the strong support of scientific and technological empowerment and conceptual innovation. According to the characteristics of representative technologies and core business elements in different periods of the development process of the financial industry, it can be divided into "it+ financial stage", "Internet + financial stage" and the "artificial intelligence + financial stage" being experienced. Each stage overlaps and affects each other to form an innovative pattern of integration and rise

today's artificial intelligence + financial development stage is based on the stable and reliable IT information system and mature interconnected development environment. It reshapes the layout of the financial industry chain and the nature of business logic. Science and technology has significantly changed the industry more than at any previous stage, and has a far-reaching impact on the future development direction of the financial industry

artificial intelligence + financial industry drivers

the government and all sectors of society jointly promote the implementation of artificial intelligence technology in the financial industry

the increase in the balance of non-performing loans forced financial institutions to take more effective risk control measures

in these eight years, the balance of non-performing loans of China's commercial banks rose from 427.9 billion yuan to 1957.1 billion yuan, of which the balance of non-performing loans in June 2018 increased by 357% compared with December 2011; The non-performing loan ratio rose from 1% to 1.86%, showing an overall upward trend. From the trend of recent years, traditional financial institutions have many problems in risk management due to insufficient attention to system and process construction, insufficient ability to timely monitor default risk, and the establishment of systematic risk early warning mechanism. At the same time, under the circumstance that the central bank's macro Prudential assessment system (MPA) has the function of experimental data calculation and analysis and the increasingly strict supervision, financial institutions need to change their previous management ideas and continuously enhance their active risk management and control ability through the use of new scientific and technological means such as artificial intelligence in order to meet future challenges

AI + related technologies in the financial industry sort out

AI and big data and other technologies are integrated to jointly promote the development of the financial industry

in the AI + financial industry, AI and big data, cloud computing and blockchain technologies are not separated from each other, but are more interdependent. Big data can provide rich nourishment for artificial intelligence technology in machine learning training, algorithm optimization and other aspects; Cloud computing provides super computing and storage capabilities for big data, significantly reducing operating costs; Blockchain solves the security problems of information disclosure and tampering in big data, cloud computing and artificial intelligence technologies, making the financial transaction hanger boom more secure. As the core driving force for the future development of the financial industry, artificial intelligence technology, together with other related technologies, will jointly promote the transformation and upgrading of the financial industry

artificial intelligence + sorting out the core technologies of the financial industry

artificial intelligence technology helps realize the intellectualization of financial scenarios

in terms of artificial intelligence, machine learning, knowledge map, natural language processing and computer vision are widely used in relevant scenarios of the financial industry. As the core of artificial intelligence, machine learning (especially deep learning) plays an extremely important role as the key technology to realize all kinds of intelligent applications in the financial industry; Knowledge atlas uses knowledge extraction, knowledge representation, knowledge fusion and knowledge reasoning technology to build basic knowledge resources to realize intelligent application; By analyzing words, sentences and texts, naturallanguageprocessing provides a strong support for improving the efficiency of customer service, investment research and other fields; Computer vision technology is widely used in authentication and mobile payment by using convolution neural network algorithm

investment and financing in artificial intelligence + financial industry

the investment fever continues unabated, and financing is concentrated in the early stage

benefiting from the rapid development of artificial intelligence technology and the growing maturity of domestic capital market in recent years, the capital side's investment fever in artificial intelligence + financial industry continues to rise. From 2011 to the third quarter of 2018, a total of 130 financing events occurred. Since 2016, the number of financing events has exceeded 30 every year. It is expected that it will maintain a stable growth trend in the future

from the perspective of financing rounds, the financing of artificial intelligence + financial industry is mainly concentrated in Angel round and a round, accounting for 38% and 27% respectively, indicating that investment institutions are generally optimistic about excellent start-ups in the early development stage of the industry and hope to accelerate the incubation process of medical technology enterprises in the industry through capital layout

intelligent risk control and intelligent investment advisers are sought after, and leading enterprises have increased their financing efforts

from the perspective of the type of technology enterprises in the artificial intelligence + financial industry, under the influence of factors such as the continuous increase in regulatory policies and the increase in the diversified development needs of public financial management, intelligent risk control and intelligent investment advisers account for more than half of the rounds, followed by intelligent investment research, intelligent marketing and other fields. Due to the relatively mature market structure of intelligent payment, There are few financing rounds

in the first three quarters of 2018, the financing amount of ant financial services, Du Xiaoman finance, JD finance and financial all in one account was more than RMB 1billion. The leading enterprises did not show better performance than traditional special polymers in the artificial intelligence + financial industry market pattern by virtue of their capital advantages

artificial intelligence + business model of the financial industry

there are a variety of technology participants, forming differentiated services and profit models

at present, not only are technology giants and benchmark enterprises in sub sectors as technology providers empowering the financial industry, but traditional financial institutions are also using their own resources to create or cooperate with Internet technology companies to form a new financial service model, accelerating the diffusion of artificial intelligence technology, Enable more financial enterprises to share technological dividends

based on the open technology platform, stable customer acquisition channels and continuous innovation activities, the industry resource advantages of financial institutions are combined with the technology precipitation advantages of Internet technology companies to redefine the value chain creation mode. While improving customer use efficiency and service satisfaction, the new business logic is rebuilt to promote the sharing of value resources between the two sides, and gradually form an ecological and market pattern of artificial intelligence + financial industry. On this basis, various technology providers have formed differentiated service capabilities and diversified profit models around key links such as infrastructure, flow realization and value-added services, and continuously expanded new business models and blue ocean markets to create greater value for the industry by using the long tail effect

: intelligent risk control

uses a variety of artificial intelligence technologies to comprehensively improve the efficiency and accuracy of risk control

risk, as an inherent characteristic of the financial industry, is accompanied by financial business. Risk prevention and control is the core problem faced by traditional financial institutions. Intelligent risk control mainly benefits from the rapid development of emerging technologies represented by artificial intelligence in recent years. It has been widely used in credit, anti fraud, abnormal transaction monitoring and other fields

compared with traditional risk control methods, intelligent risk control has changed from the passive management mode used to meet the requirements of compliance supervision to the active management mode of monitoring and early warning based on new technologies. Taking credit business as an example, there are problems in the traditional credit process, such as fraud and credit risk, cumbersome application process, long approval time, etc. through the use of artificial intelligence related technologies, we can deeply mine key information from multi-dimensional massive data, find out the relationship between the borrower and other entities, improve the accuracy of risk identification from pre loan, in loan and post loan links, and use intelligent collection technology to replace 40%~50% of the manpower, Save labor costs for financial institutions. At the same time, AI technology can shorten the approval time limit of small loans from the past few days to 3-5 minutes, further improving the customer experience

intelligent payment

with biometric technology as the carrier, it provides solutions for diversified consumption scenarios

under the influence of the accumulation of massive consumption data and the superposition of diversified consumption scenarios, traditional digital payment methods such as Bracelet payment, code scanning payment and NFC near-field payment can no longer meet the actual consumption needs. Face recognition, fingerprint recognition, iris recognition With the gradual rise of intelligent payment with biometric carriers such as voiceprint recognition as the main means, technology companies have provided diversified scenario solutions for merchants and enterprises to comprehensively improve the billing efficiency of merchants and reduce the waiting time of customers

as an effective connection to carry online and offline services, intelligent payment, combined with intelligent terminals, IOT and data centers, can present settlement and payment, member rights, scenario services and other functions to consumers from multiple perspectives. At the same time, it can timely feed back payment data and consumption behavior to the background, providing support for merchants' account checking, member marketing management, business data analysis and other work. In the future, a new model represented by senseless payment

Copyright © 2011 JIN SHI