Brief introduction:Through the construction of its own data platform, IT gets through the previous independent construction of the IT system, so that all parties of data convergence and connectivity, and eventually form a powerful data decision engine, not only let consumers get a satisfactory service experience, but also significantly reduce the operating costs of the platform side.
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Taobao shop entry 10 method, shop operation must see 20, novice fast master 30 guidelines…… Documents about e-commerce operations fill the desktop of Liu Hao, a college student about to graduate.
Liu Hao’s hometown is a small village in the mountainous area of western Zhejiang. There are only 42 families in the village. Because the whole mountainous area is covered by bamboo forests, every family has inherited the craft of weaving bamboo slivers from generation to generation, from bamboo MATS, vegetable baskets, baskets, and various craft gadgets. In previous years, the town was often door-to-door to receive finished products, depending on the size of the object site pricing, 5 yuan -30 yuan is a common market, but Liu Hao knows that these things sold in the city, often are the starting price of 50 yuan.
Unlike other graduates, Liu has always had a small entrepreneurial dream in his heart.
“Why can’t I open a Taobao shop to help the villagers sell goods?”
However, he needed an initial capital of around 20,000 yuan to start his business. However, his parents did not support Liu’s idea. In their opinion, college students should stay in the big city to find a safe job after graduation.
Fortunately, today’s Internet financial services have become more standardized and convenient, and the application of small loans for individuals is not as complicated as in the past. With the loan assistance service provided by formal financial institutions, Liu Hao got the required loan from the bank that same afternoon and started his own business.
Promote the comprehensive upgrade of financial services with data technology
Thanks to the full implementation of digitization in the financial industry, as well as the increasingly normal and standardized lending services provided by financial institutions, more and more ordinary people can enjoy convenient credit loan services like Liu Hao.
In the number of big data technology in charge of Wan Peng, today’s financial institutions can through deep combination of data technology, change the former financial industry manual credit audit of the inefficient state, reshaping the two-way service path between banks and borrowers.
Wan Peng, head of big data at Wo Technology
“On the one hand, we identify new demand groups for banks and provide up-front services, including credit scoring, which greatly alleviate the audit pressure for banks. On the other hand, with our insight into the needs of borrowers, we are able to match them with the best banks so that they can get the best quality credit in the shortest time.”
In 2015, the company was formally established to provide financial technology services for licensed financial institutions and consumers with loan needs, focusing on consumer credit business.
“We have invested a lot of research and development resources in artificial intelligence, big data and other fields, hoping to give full play to the advantages of digital, automated and intelligent financial technology, provide the best financial services for a larger base of groups, and practice financial inclusion.” As of May 2021, the company had established cooperation with more than 70 banks and other financial institutions, covering more than 80 million registered users, Wan said.
Data in the middle enables visible data to flow through the business
Credit service as one of the main business of several grain science and technology, is essentially to solve information between Internet users and not matching problem, several grain through digital means sufficient insight into consumer demand for credit, screening accuracy for financial institutions qualified loan users at the same time, provide users with high-quality financial services more convenient.
And behind this service model, data is becoming the most efficient bridge between the demand side and the service side.
For Wo, although relying on technology in the field of consumer finance for many years, but how to put the business process generated by the data more efficient feedback business, Wo also needs a more perfect data methodology and product tools support.
At this time, Ali cloud data into the number of Wo vision.
Because very important data assets to help lend strong support ability of the business, in July 2020, the number of grain science and technology cooperation with ali cloud formally established, start the China project data, Wan Peng as a head of big data, data to lead the development of the project construction in China, to help grain in digital upgrade 2.0 strategic backdrop, lock data ability advantage.
In the phase 1.0 of digital strategy, the company built the practical underlying data system and business application system. However, in many cases, the data requirements proposed by the business were often solved in the form of one-to-one, which not only lagged the response speed, but also led to a large number of chimney-like systems. Number increase with the level data, the traditional warehouse construction idea cannot efficiently support the enterprise digital requirements, number of grain management consciousness to solve the problem of data island, through the synergy between each system and organization, the release of the company’s share ability and innovative ability is the key of digital strategic breakthrough.
Wan Peng mentioned two main reasons for choosing Ali Cloud Data Middle Platform as the underlying technical support of the digital strategy:
“Alibaba was the first to put forward the concept of data in Taiwan. It has the deepest understanding of China in Taiwan and the most comprehensive solutions. The experts sent to the site also have rich practical experience.
The methodology system of Ali cloud data platform is also one of the ability that the number of he values very much. Based on One Data methodology, AliCloud Data Platform forms Data acquisition, governance, asset management and other capability matrices through Dataphin products, so that Data platform projects can be quickly implemented in enterprises.
Wan Peng mentioned: “ali cloud data China bring One Service interface data services, before we since research data platform, providing data interface in online business link is too long too complicated, at present China by ali cloud data products Dataphin building data input and output of the link is smooth and fast, the product itself with integrated channel.”
After 7 months of co-construction, the big data team of Shuhe restructured and upgraded the traditional data warehouse system, unified the data asset management platform, comprehensively sorted out the company’s core business processes with the help of the project, connected all the business processes and the corresponding data behind them to unify a set of information system. Each business process can see the specific data warehouse table, indicators, the current value of indicators, month-on-month and year-on-year information on the information platform. Once these indicators are abnormal, it can quickly automate the attribution, locate the problem link, and innovatively establish the data operation mode.
Reviewing the digital construction work in the early days of Shuhe, Wan Peng said: “In the past five years, we paid more attention to what data was generated in the company’s operation process, which business processes could be digitized, and data compliance issues. Back five years, the data quantity will be more and more big, the number of traditional warehouse construction ideas can no longer support the enterprise to save number, pipe number, with several requirements, we need a more advanced data tools and methodology, to solve the information asymmetry problem between customers, we eliminate the understanding deviation, through data reduction and predict the behavior of users and ideas. “
Inclusive finance for one billion Internet users
At present, the demand for loan assistance is booming and there are many scenarios. It is impossible to ensure that borrowers can enjoy the required financial services in time by relying solely on manual labor. For example, when a user sees the loan information from social platforms, short video platforms, offline elevator advertisements and other media channels, he clicks on the webpage to browse the relevant information, and submits the loan application online after a period of time.
In the face of such a user, how should the number of Wo for him to provide the required lending services?
The “match” here actually includes a lot of dimensions, such as credit limit, approval rate, lending speed and so on. The actual loan needs of each user are different, so it is impossible to meet the non-standard loan needs through unified service content, and all of this requires data to support a series of subsequent operation decisions and form a personalized loan service model.
Through the construction of its own data platform, IT gets through the previous independent construction of the IT system, so that all parties of data convergence and connectivity, and eventually form a powerful data decision engine, not only let consumers get a satisfactory service experience, but also significantly reduce the operating costs of the platform side.
The gain of data center for risk control scenario is also not negligible.
At the early stage of the development of the industry, risk control means were single, and customers were concentrated on the credit list and corporate customers. Since then, online customer acquisition has gradually become the mainstream channel, and the risk control means has changed from collateral guarantee to big data modeling. The customer boundary has been continuously expanded, and the industry has ushered in the opportunity of rapid development. Behind this, there are higher requirements for accurate credit granting and risk pricing of borrowing customers.
When more and more borrowers flood into the platform, whether the risk cost is controllable is the problem that the lending platform needs to think about. Only through accurate assessment in the pre-loan approval process, a substantial increase in the approval rate, a basically stable risk level and a reduction in the cost of credit verification, can the lending assistance platform obtain more substantial operating profits.
“After switching to the middle platform mode, we not only achieved data integration, but also promoted data standardization and capitalization through data governance means. This series of measures strengthen the intelligent risk control mode based on data assets. Based on the unified model of data center and unified data service, the more diversified the newly constructed risk control model can access to data, the lower the risk indicators such as bad debt rate and intermediary fraud rate in the later period. For example, the intermediary model can monitor suspected financial intermediaries on the application users, with an accuracy of more than 80%. “
In the stage of digital strategy 2.0, digital intelligence upgrade is completed on the basis of the original information based on the data middle platform. The more intuitive embodiment is to achieve full automation or semi-automation of operation actions as far as possible. For example, at the technical level, I will build my own strategy and execution system. Product level, to provide more digital, intelligent products; At the service level, users can feel the convenience brought by digital transformation through call center, intelligent robot, intelligent knowledge base, intelligent quality inspection, intelligent customer service, etc. At the risk control level, we will continuously deepen the refined operation and improve the risk control model…
At the system level, data decision engine and business execution system are decoupled. Data decision engine access a series of business execution system, data in China as the core to complete data analysis, intelligent decision, and then form the instructions as the output, given to decision-making and command system, so that the business execution system gradually completed from “man + system” to “+” robot system automation, intelligent upgrade process, gradually reduce the dependence on human decision-making.
The benefit brought by this approach is that with the gradual advancement of the mid-Taiwan project, enterprises can conduct digital maturity self-examination, standardize and define the missing or non-standardized business processes through research sorting and unified modeling, and reach consensus at the enterprise level. The business process and key indicators of the enterprise are connected in series through data to form Kanban. The management can quickly locate the problem in the business process through data drive, efficiently find the business changes, and form the corresponding business strategy or management strategy adjustment.
The construction of the data platform is not a day’s work, the digital 2.0 strategy of the number of he technology is also continuing to advance. And how to build a more complete “digital intelligence system” in the future is a proposition that every data practitioner and enterprise management should think about. The core of the continuous operation of data center lies in the construction, governance and operation of data assets. Shuhe Technology will continue to practice and refine the best practices of data center operation, and drive the rapid development of business while fully mining the value of data.
Related products: Dataphin for intelligent data building and management
Data center platform is the only way for enterprises to become digital intelligent. Alibaba believes that data center platform is an intelligent big data system that integrates methodology, tools and organization, and is “fast”, “accurate”, “complete”, “unified” and “universal”.
At present, we are exporting a series of solutions through AliCloud, including general data mid-platform solution, retail data mid-platform solution, financial data mid-platform solution, Internet data mid-platform solution, government data mid-platform solution and other subdivided scenarios.
Among them, AliCloud data middle platform product matrix is based on Dataphin and started with Quick series as business scenarios, including:
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