Tongdun Technology: Rebuild The Financial Risk Management With AI
COVID-19 and China

On June 15, 2018, EO Company (亿欧) held the 2018 Global AI + New Business Summit in Shanghai themed as the intellectualization of financial industry driven by the technology of AI, blockchain, big data.

Under the guidance of Shanghai Municipal Commission of Economy and Informatization (上海市经济和信息化委员会), Shanghai Municipal Commission of Economy and Informatization (上海市商务委员会), Shanghai Changning Municipal Government (上海市长宁区人民政府), Association of Shanghai Internet Financial Industry (上海市互联网金融行业协会), Shanghai Youth Federation of Changning District (上海市长宁区青年联合会) and Yiou co-held the summit together.

ZHU Wei (祝伟), the co-founder and vice president of Tongdun Technology, gave out a speech featured as How to rebuild the financial risk management in the new era.

Below is the main text of ZHU Wei's speech:

Thanks for the host and good afternoon!

The topic I want to share with you is "How to rebuild the financial risk management in the new era". In recent years, FinTech and TechFin are very popular. During the combining process of the internet technology and finance, Fintech is set to rebuild the industry using data analysis and AI algorithm.

The market develops rapidly, and the stages of different industries vary from data infrastructure and data application. Many industries grab the chance of deploying from data infrastructure to data chain analysis.

As we can see from the figures below, we can see that the data infrastructure was quite weak in various industries in the past, and with the rapid development of online business, there brings the challenge of data management, underlying data infrastructure construction, including how to combine the data analysis to face the challenge like scenario analysis.

Based on this developing background, Tongdun Technology introduced the AaaS(Analytics-as-a-Service) concept, whilst other companies mainly focus on the basic infrastructure construction and SaaS(Service-as-a-Service), adding more software ability on the cloud, and serve their cooperation partners. As for Tongdun technology, we want to connect the problem scenarios on the basis of SaaS, and to solve specific issues in problem scenarios using data analysis and algorithm, that's what we called as AaaS.

During our development, Tongdun Technology has positioned ourselves as a technology company, and we hope to provide service for different partners through cooperations. Intelligent Scenario Analysis Service is a data sorting and management embedded process, where data is the core value and base of algorithm and artificial intelligence.

Whilst coming to the level of data, we combine the first-hand data and third-party data to connect the technology on different scenarios, including applying AI technology on the pre-loan, during-the-loan and post-loan scenarios, to solve the safety, fraud, cheat related issues for the customers on their business networking process. Use data analysis to solve the problems in specific scenarios is the framework of our AaaS Theory.

To be more specific on the business level, the main risk is the potential fraud could appear on online business. Tongdun combines the fraud related information, fingerprint, IP Portrait, users’ internet behavior to analyze and predict the risk. With the help of analysis ability on different scenarios in the life-cycle of loaning, Tongdun provides clients with analyzing service. The basic technology of Tongdun can analyze text, images and voice user interface, with technologies of machine learning and AI algorithm.

In 2016, we gradually enable our data analysis ability and the calculation capacity and system that has been trained on the cloud for years to our cooperating partners. We trained our machine learning with data coming from our clients, and improve decision making analysis, process calculation model, graph computing to apply into different scenarios.

For our cooperating partners, we provide both standardized products and customized service. we provide major customers customized and scenarioized analysis service, which can give out deeper analysis output based on the specific data of the customers in the specific scenarios using conjunctive models. We also provide standardize service includes the Intelligent analysis like the loan scenario solutions, transaction risks of online business and follow-up operation.

Tongdun provides a set of solutions including the intelligent marketing analysis service (customers value analyzation) and the solutions of pre-loan, during the loan and post-loan cycle for the whole loan life-cycle.

In the section of customer acquisition, Tongdun intelligent marketing analysis service can help our clients in analyzing thoroughly during the process of acquiring new customers based on the data collected on the cloud combined with the algorithm and problem scenarios. By using data analysis, our clients can maximize their conversion rate to reduce the cost of acquiring new customers.

In the post-loan section, Tongdun can provide a set of intelligent collecting methods, for example, the overdue managing product which can combine the scorecard to sort, contact and communicate in an intelligent way. The intelligent collecting product is more standardized with lower cost compared to the traditional method. Standardized products can minimize the risk of loan collection and policy requirements.

Tongdun has a long corporation history with financial institutions. Deeply rooted in the internet life cycle, Tongdun is capable to provide a set of solutions for e-commerce, O2O and traveling industry. We can provide specific models for different scenarios and reduce risks of online business.

Last but not least, I am going to introduce our team. Currently, our company has almost 1000 employees, more than 70% of them are from R&D Department. As co-founders, both JIANG Tao (蒋韬) and I are engineers. Tongdun provides services for almost 10,000 companies.

Above is what I can share with you, and hope we could have deep cooperation and communication in the future.


- Author: TANG Shiyu; ZHU Wei contributed to this article. Write to TANG Shiyu at

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