Introduction to has built its own data center and opened up the independent IT system in the past, so that the data of all parties can be integrated and connected, and finally a powerful data decision-making engine is formed, which not only allows consumers to obtain a satisfactory service experience, but also greatly Reduce the operating cost of the platform.
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Taobao store opening 10 methods, 20 must-see store operations, 30 guidelines for novices to quickly grasp... Various e-commerce operation documents are filled with the computer desktops of Liu Hao, a college student who is about to graduate.
Liu Hao’s hometown is a small village in the mountainous area of western Zhejiang. There are only 42 families from the village head to the end of the village. Because the entire mountain area is covered by bamboo forests, every family has inherited the craft of weaving bamboo sticks for generations. , Vegetable baskets, baskets, and all kinds of craft gadgets. In previous years, people in the town often came door-to-door to collect finished products, depending on the size of the objects, on-site pricing, 5-30 yuan is a common market, but Liu Hao knows that these things are sold in the city, often at a starting price of 50 yuan.
Unlike other graduates, Liu Hao has always had a small entrepreneurial dream in his heart.
"Why can't you open a Taobao store to help the villagers sell goods?"
It’s just that, opening a store requires a start-up fund of about 20,000 yuan, but his parents do not support Liu Hao’s idea. In their opinion, college students should stay in the big city to find a stable job after graduation.
Fortunately, the development of Internet financial services is becoming more standardized and convenient. Personal micro-loan applications are not as complicated as in the past. Through the loan assistance services provided by formal financial institutions, Liu Hao got what he needed from the bank that afternoon. The loan started his own entrepreneurial road.
Use data technology to promote a comprehensive upgrade of financial services
Thanks to the full implementation of digitalization in the financial industry and the increasingly normal and standardized loan assistance services of financial institutions, more and more ordinary people can enjoy convenient credit loan services like Liu Hao.
According to Wan Peng, the person in charge of big data at Shouhe Technology, today's financial institutions can change the inefficiency of manual credit review in the financial industry through deep integration of data technology, and reshape the two-way service channel between banks and borrowers.
Wan Peng, Head of Big Data, Shuhe Technology
"On the one hand, we explore new demand groups for banks and provide early-stage services including credit scoring, which greatly eases the pressure of bank review; on the other hand, we can provide insights into the needs of borrowers and can match them most appropriately The bank makes it possible to obtain the highest quality credit loan in the shortest time."
In 2015, Shuhe Technology 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 to provide the best financial services for a larger base group and practice financial inclusiveness." Wan Peng said that as of May 2021, Shuhe Technology has established cooperation with more than 70 banks and other financial institutions, covering more than 80 million registered users.
data center blessing allows visible data flow in the business
As one of the main businesses of Shouhe Technology, the loan assistance service is essentially to solve the problem of information mismatch between funds and Internet users. Shouhe uses digital means to fully insight into consumer credit needs, and provides accurate screening for financial institutions. Qualified loan users also provide users with more convenient and high-quality financial services.
Behind this service model, data is becoming the most efficient bridge connecting the demand side and the service side.
For Shuhe, although it has been deeply involved in the consumer finance field with technology for many years, how to feed back the business more efficiently with the data generated in the business process requires a set of more complete data methodology and product tool support.
At this time, Alibaba Cloud Data Center has entered the horizon of Shuhe.
Because we attach great importance to the strong support capabilities of data assets for the loan assistance business, in July 2020, Shuhe Technology and Alibaba Cloud formally established a cooperation to start the data middle-stage project. Wan Peng, as the head of the big data department, takes the lead in the construction of the data middle-stage project In order to help Shuhe to lock in the advantages of data capabilities under the background of the digital upgrade 2.0 strategy.
In the 1.0 phase of the digital strategy, Shuhe has built a practical underlying data system and business application system, but in many cases the data requirements raised by the business are often solved in a one-to-one manner, which not only lags in response speed, but also leads to a lot of chimney-like systems. With the increase in the magnitude of data, the traditional data warehouse construction ideas cannot efficiently support the digital needs of enterprises. The management of Datahe realizes to solve the problem of data islands, open up the collaboration between various systems and organizations, and release the company's sharing capabilities And innovation ability is a key measure to achieve breakthrough progress in digital strategy.
Wan Peng mentioned two main reasons for choosing Alibaba Cloud Data Center as the underlying technical support of the digital strategy:
"Alibaba was the first to propose the concept of data centering, with the deepest understanding of the centering stage and the most comprehensive solutions. The experts dispatched to the scene also have rich practical experience."
The methodology system of Alibaba Cloud Data Center is also one of the abilities that Shouhe values very much. Based on the One Data methodology, Alibaba Cloud Data Center uses Dataphin products to form a data collection, governance, and asset management capability matrix, enabling the data center program to be quickly implemented in the enterprise.
Wan Peng mentioned: "Alibaba Cloud Data Center has its own One Service data interface service. The data platform we developed previously had too long and complicated links to provide data interfaces for online businesses. Currently, Alibaba Cloud Data Center products Dataphin builds data input and output links that are smooth and fast, and the product itself has its own integrated channel."
After 7 months of co-creation and co-construction, the big data team of Shuhe has reconstructed and upgraded the traditional data warehouse system, unified the data asset management platform, and at the same time, with the help of the project, the company’s core business processes have been comprehensively sorted out, and all business processes and The corresponding data behind is connected in series to unify a set of information systems. For each business process, you can see specific data warehouse tables, indicators, current values of indicators, month-on-year comparisons and other information on the information platform. Once these indicators are abnormal, It can quickly automate attribution, locate problematic links, and innovatively establish a data operation model.
Looking back at the digital construction work in the early days of the establishment of Shuhe, Wan Peng said: "In the past five years, we have paid more attention to what data is generated in the company's business process, which business processes can be digitized, and data compliance issues. Look at the next five years. , The amount of data will become larger and larger, and the traditional data warehouse construction ideas can no longer support the needs of enterprises for storage, management, and use of data. We need a set of more advanced data tools and methodology to solve the problem between us and consumers. The problem of asymmetry between information, eliminates understanding bias, and restores and predicts user behavior and thoughts through data.
for one billion Internet groups
The current demand for loan assistance is strong and there are many scenarios. It is impossible to ensure that borrowers can enjoy the required financial services in a timely manner by relying solely on manual labor. For example, when a user saw loan information from social platforms, short video platforms, offline elevator advertisements and other media channels, he clicked into the web page to browse the relevant information, and submitted a loan application online after a period of time .
Facing such a user, how should Shuhe provide him with the necessary loan assistance services?
The "matching" here actually includes a lot of dimensional judgments, such as credit limit, approval rate, loan speed, and so on. The actual loan needs of each user are different, and it is impossible to meet the non-standardized loan needs through a unified service content. All of this requires data to support a series of subsequent operational decisions and form a personalized loan assistance service model.
By constructing its own data center and opening up the independent IT system in the past, Shouhe enables data from all parties to converge and connect, and finally form a powerful data decision-making engine, which not only allows consumers to obtain a satisfactory service experience, but also greatly reduces the platform’s Operating costs.
The gain of the data center for the risk control scenario cannot be ignored.
In the early stage of the industry's development, the risk control measures were single, and customer acquisition was concentrated on the credit list and corporate customer acquisition. Since then, online customer acquisition has gradually become a mainstream channel, risk control methods have changed from collateral guarantees to big data modeling, customer boundaries have continued to expand, and the industry’s rapid development opportunities are behind the precise credit granting and risk pricing of borrowing customers Higher requirements.
When more borrowers flock to the platform, whether the risk cost is controllable is a question that the lending platform needs to think about. Only when the pre-loan approval process is accurately assessed, the approval rate is greatly increased, the risk level is basically stable and the credit verification cost is reduced, the loan assistance platform can obtain more substantial operating profits.
"After switching to the middle-station model, we not only achieved data integration, but also promoted data standardization and assetization through data governance. This series of measures strengthened the intelligent risk control model based on data assets, based on the unified model of data middle-station , Unified data services, the newly constructed risk control model can access the richer the types of data, and it can minimize the risk indicators such as the bad debt rate and the intermediary fraud rate in the later period. For example, the intermediary model can monitor the applicants for suspected financial intermediary, and it is accurate The degree can be over 80%."
In the digital strategy 2.0 stage, based on the original informatization, Shouhe completed the digital intelligence upgrade relying on the data center. The more intuitive embodiment is to make the operations as fully or semi-automatic as possible. For example, at the technical level, build your own strategy and execution system; at the product level, provide more digital and intelligent products; at the service level, let users feel digital through call centers, smart robots, smart knowledge bases, smart quality inspections, smart customer services, etc. Convenience brought by transformation; At the risk control level, we continue to deepen refined operations and improve the risk control model...
From the system level, the data decision engine and the business execution system are decoupled. The data decision engine is connected to a series of business execution systems to complete data analysis and intelligent decision-making with the data center as the core, and then form operation instructions as output, which are issued to the decision-making command system, so that the business execution system gradually completes the transition from "people + system" "To "robot + system" automated and intelligent process upgrades, and gradually reduce the dependence on manual decision-making.
The benefit of this is that with the gradual advancement of the China-Taiwan project, companies can conduct self-inspection of digital maturity, and standardize and define missing or non-standard business processes through investigation and combing and unified modeling, and at the enterprise level Reach a consensus. The business process and key indicators of the enterprise are connected through data to form a Kanban. The management can quickly locate the problem in the business process through data drive, efficiently detect business changes, and form corresponding business strategies or management strategy adjustments.
The construction of the data center is not a day's work, and the digital 2.0 strategy of SHUHE Technology is also continuing to advance. How to build a more complete "digital intelligence system" in the future is a proposition that every data practitioner and business management must think about today. The core of the continuous operation of the 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 the business while fully tapping the value of the data.
Related products: Intelligent data construction and management Dataphin
Data center is the only way for enterprises to achieve digital intelligence. Alibaba believes that data center is a combination of methodology, tools, and organization, which is "fast", "quasi", "full", "unified", and "passed". Smart big data system.
Currently by Ali cloud external output range of solutions, including common data desk solution , retail sales data desk solution , financial data desk solution , Internet data desk solution , Subdivision scenarios such as government data mid-channel solutions.
Among them, the Alibaba Cloud Data Center product matrix is based on Dataphin and the Quick series is used as a business scenario cut-in, including:
- -Dataphin, a one-stop, intelligent data construction and management platform ;
- -Quick BI, intelligent decision-making anytime, anywhere ;
- -Quick Audience, comprehensive insight, global marketing, and intelligent growth ;
- -Quick A+, a one-stop data-based operation platform cross-multi-terminal global application experience analysis and insight;
- -Quick Stock, an intelligent goods operation platform ;
- -Quick Decision, an intelligent decision platform ;
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