In 2017, artificial intelligence (AI) has become a national strategy, and has started to be implemented in more and more industries. The traditional financial industry is impacted by Internet technology, and has embarked on the road of transformation to digital and intelligent transformation. InfoQ spoke with Xiang Jiangxu, CTO of CreditEase, about the application of AI in the digital transformation of the financial industry.
“AI is better suited to serving scenarios than spawning new industries”
Follow the trend of development and realize digital transformation
Xiang Jiangxu believes that from the impact of technology on the industry, the development of the Internet has gone through three important stages.
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Informatization: the most important sign is the emergence of PC. Many enterprises began to use ERP, CRM, OA system in the background, to get rid of paper and manual operation towards automation, in order to improve efficiency and reduce costs, data also began to settle down.
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Internetization: In this stage, enterprises can provide services through the connection with the Internet. The classic example is e-commerce: the transfer of services and goods from offline to online. At the same time, a huge amount of data on products and user behavior has been generated, giving rise to technologies such as search engines and recommendation algorithms, enabling enterprises to use this data to help adjust and upgrade their businesses and services.
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Intelligent: Represented by AI and combined with various terminal devices, personalized customized services can be provided in specific scenarios. With the development of AI and data science, big data is deeply involved in every link of enterprise operation and decision-making, and plays a key role in the development of enterprises, thus the industry has entered the stage of digital wave.
At each stage, there are some enterprises that can seize the technological trend at the time and achieve their own success.
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At the beginning of the Internet, people mainly get information on the Internet. Sina, netease and Sohu, three major portal websites, conform to the development of browser technology and achieve great success through the presentation of information.
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After the emergence of search engine technology, accurate matching can be obtained through keyword search. New business models (such as advertising business of bidding ranking) emerge at the historic moment, giving birth to a group of companies such as Google and Baidu. The development of Internet companies has made online shopping possible, leading to the emergence of Amazon, Alibaba, JINGdong and other e-commerce companies, and the rise of social software has led to the emergence of Tencent, Facebook and other social giants.
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In the era of intelligence, the popularity of mobile Internet technology has spawned a number of smart phone companies.
Although there are already a number of AI unicorns, in Jiang’s view, AI technology is not the same as the above mentioned technologies. It is more suitable for use in a certain situation, rather than creating a new industry, so it is difficult to create another set of giant companies. With the current technological trend and market environment, enterprises should follow the trend of development and realize digital transformation by combining AI, big data and other technologies.
Challenges facing digital transformation of financial industry
During his research on the financial industry, Xiang Jiangxu divided the companies in the industry into three categories:
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“Traditional” financial firms. Including banks, securities brokers, insurance companies and other financial institutions.
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Tech Finance, aka TechFin inc. It is a financial company in nature, but technology is very strong, and technology plays a central role. Such companies include Ant Financial, JD Finance, Suning Finance and CreditEase.
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There are also FinTech companies, or FinTech companies, such as solution provider Tongdun, which do not offer financial products but technology solutions for the financial industry.
In the era of digitalization and intelligence, the financial industry also inevitably faces the demand of digital transformation, among which the transformation demand of traditional financial companies is more intense. Financial industry, especially traditional financial institutions, face the following challenges in the process of transformation:
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There needs to be a shift in mindset. Traditional financial institutions tend to be conservative in technological innovation due to the excessively large volume of data and the safety-oriented principle of the financial industry.
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There is a shortage of technical talent. Artificial intelligence and data science are in the ascendant, and related technologies are still in the stage of development and improvement. There is still a shortage of AI and big data talents.
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New technologies are difficult to access. Traditional financial institutions have a long history of development, complicated structure and difficult access to new technologies.
The technology leader should lead the transformation with foresight and decision-making
Xiang jiangxu has also accumulated rich experience in leadership over the past 20 years. On the topic of how technology leaders maintain forward-looking technology, Xiang jiangxu believes that the most important thing is to keep learning. After the emergence of any technology, we must first see where it is applicable and what specific problems it can solve. One of the pitfalls that techies tend to fall into is using the latest, coolest tools to solve problems that don’t require complex solutions, which is something to avoid. Technology leaders need to keep track of new technologies, immerse themselves in specific industries and scenarios, and choose technologies according to the scenarios rather than blindly following the crowd.
When asked “in the process of enterprise technology transformation, what factors will affect the implementation of technology decisions, and how do technology leaders deal with them?” Xiang Jiangxu believes that there are three aspects:
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Identify technical advantages and avoid selection disputes: Some technical people have tech religion. In the process of technological transformation, there will be disputes over technology selection. At this time, technical leaders should identify the advantages and disadvantages of new technologies based on their business.
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Top-down promotion and bottom-up implementation: Technical transformation needs top-down promotion, and clear goals and consensus are reached with technical team members to jointly realize technical transformation.
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Avoid the risk of change and balance the pace of change. Change means stepping out of your comfort zone, and the transition between new and old technologies can be risky. Technology leaders need to maintain a balance, not rush, not procrastinate, and encourage their teams to work through the pain of change.
‘AI is a natural fit for finance’
Finance should be combined with AI and big data
Xiang Jiangxu believes that the financial industry is born to deal with numbers and has very high requirements for digitalization. The advantage of AI is that it can analyze and calculate massive amounts of data, build models and do things that humans cannot do. At the same time, AI’s lack of emotion can be a huge advantage in the financial industry, which is highly rational and unemotional, and where greed and fear must be overcome. For example, when quantifying investment and reviewing credit, AI’s decisions are more rational and correct without personal emotional considerations. In addition, compared with traditional industries such as manufacturing, the financial industry has a higher degree of information technology and a better digital foundation, which can be more easily transformed into intelligent industries.
Creditease itself has the genes and attributes of traditional finance. In order to realize intelligent transformation, creditEase proposed AI finance strategy based on its three major business segments — inclusive finance, wealth management and asset management, that is, to adopt AI technology according to the problems encountered in its own business scenarios. Recommend the right interest rate and product by analyzing the borrower’s needs and ability to repay. Analyze the needs of wealth management clients and tailor financial products for them. Creditease provides both real person services in offline stores and virtual services on the APP. When providing services to customers, it can use AI algorithms to build models, establish user portraits, analyze needs and recommend products, all of which are completed based on massive data.
Creditease Big data Finance
The data collection
Creditease’s business covers both online and offline. Its products are released online, online subscription, all realize digitization. Offline, every interaction with customers will be recorded by voice or text, and activities will be run through data. Clear user portraits will be created according to users’ online and offline behaviors to achieve accurate customer positioning. All the collected data and information are stored in the knowledge base to form the user knowledge graph, which provides support and basis for decision-making of different business lines.
The data used
How does Creditease integrate big data with its own business? Introduced to Jiang Xu that the collected user data is mainly used for the following aspects:
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Personalized recommendation. For example, the above mentioned customized financial products for wealth management users.
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Intelligent risk control. Creditease has its own risk control system, which is used to evaluate investment risks and user credit, and can accurately identify fraud risks.
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Smart push. Creditease has developed an intelligent customer service robot to complete message push, consultation, reminder and other services with a set of simulated human speech.
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Intelligent investment. According to the user’s risk tolerance, investment return expectation and so on, a set of investment portfolio strategy is calculated with the algorithm model, and automatic positioning is tracked and recorded every month.
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Intelligent research. Many customers who invest in the stock market need to have an in-depth understanding of the industry and specific companies. Intelligent investment research can present information to customers through collection and sorting.
Creditease data Center
Creditease has its own big data platform and is currently building a data center. According to Xiang Jiangxu, Creditease’s data center integrates data from different sources for cleaning, sorting and correlation, forming financial knowledge atlas or financial brain for use by different business lines.
Creditease’s data center is still under construction, and many components of the underlying platform have been completed and opened source. For example, big data streaming processing platform Wormhole, big data bus DBus, big data virtual mixed computing service platform Moonbox, big data visualization application platform Davinci, etc.
Creditease AI Zhongtai
At present, CreditEase has put the application of AI technology in an important strategic position, and put forward the slogan of “Finance embraces AI”. In the implementation process, creditease in addition to building data center, is also developing AI center.
What is the AI medium?
In Xiang Jiangxu’s view, the purpose of zhongtai is to provide reusable capabilities for shared services. Both technical and business medias need to componentize common parts into reusable services to be provided externally. These services can be capabilities, algorithms, models, or a set of tools. AI medium platform is to componentize, servize and instrumentalize the capabilities of AI and directly apply them to other external application scenarios.
At present, many enterprises have the problem of slow response and low efficiency in the process of intelligent application research and development. Many AI r&d teams are more like outsourcing teams, building their own bases according to the needs of different business units and gradually attacking targets, with repetitive processes and limited efficiency. Therefore, AI Zhongtai aims to provide a powerful AI capability support center that can quickly provide fire support according to business needs and achieve goals quickly.
Creditease’s definition of AI zhongtai is:
AI Center platform is the intelligent model life-cycle management platform and service configuration system. It helps front desk businesses to quickly build personalized intelligent services through the sharing and reuse of intelligent services and the automatic management of service research and development.
The hierarchical structure of Creditease AI medium platform is shown in the figure below:
The AI center sits between data model services and business solutions, connecting business data upward and communicating data downward, and each level has its own reusable mechanisms. The middle part is divided into business understanding, model learning and data processing from top to bottom. The operation monitoring on the right side provides unified encapsulation of products and models and unified external access interfaces. On the left is platform management throughout the entire process, including role rights, tenant management, process control, and resource management.
Creditease’s years of experience in the financial industry make it accumulate a lot of technology. For example, CreditEase has a set of tools, processes and platforms suitable for financial business, as well as corresponding algorithm library and model library. With the AI Central platform, the construction and modeling of financial knowledge graph can be completed based on the AI central platform. Intelligent customer service, intelligent electric sales, intelligent collection, as well as risk control model and anti-fraud model are all application scenarios of AI Center, which are developed and practiced based on the ability of AI Center. At present, AI Zhongtai has been successfully used in creditease’s intelligent customer robot (Toulmi RA) and other products.
In the future, creditease AI after internal verification mature, creditease also intends to put AI packaging, become an open platform for the industry, even open source, and peers together to discuss the construction.
“The era of AI has arrived. Embrace it boldly and practice it carefully.”
Write in the last
As a battle-hardened technician, XIANG Jiangxu has witnessed the technological changes, the “Internet +” mode and the process of transferring business from offline to online. With years of insight into the industry and a forward-looking grasp of technology trends, Xiang jiangxu is very optimistic about the integration of AI technology and the financial industry. In Xiang Jiangxu’s opinion, the era of AI has arrived. We should take AI very seriously, especially its application in the field of fintech. We should embrace it boldly and practice it carefully.
Introduction to interview Guests
Xiang Jiangxu, CTO and Executive Director of CreditEase Technology Committee, has more than 20 years of professional experience, including 18 years of studying and working in Silicon Valley. After graduation, Xiang jiangxu worked at Cisco, CA, Dell and other companies in software and networking. In 2010, he joined Microsoft as assistant to the chairman of Microsoft Asia Pacific R&D Group and director of Group Technology Strategy, as well as chief project General manager of Cloud computing and Enterprise Business Division, focusing on the application and implementation of cloud computing, IoT and AI. After returning to China, HE entered the field of smart retail, serving as CTO before Secoo, and then as executive vice president of SUNing IT Headquarters and president of Suning Technology Research Institute. He led the development of suning’s unmanned stores, intelligent speakers, intelligent shopping guide and other businesses, and applied computer vision and artificial intelligence natural language technologies to retail scenes. In 2018, Xiang Jiangxu was appointed CTO of CreditEase to explore and innovate by combining AI with the financial industry.
Guests | Jiang Xu
The original release | AI the front