w88 casino News Network (provided by the w88 casino of Finance)2021At 19:30 on the evening of April 30, 2020, Professor Qiu Zhigang’s special lecture in the Financial Culture Festival lecture series was held in the form of an online Tencent conference. Professor Qiu Zhigang, associate professor and vice president of the Hanqing Research Institute of Renmin University of China. His research interests include agency portfolio management, asset pricing theory and financial technology, and he has published many international journal papers. In this meeting, Professor Qiu Zhigang shared his thoughts on financial technology based on a series of cases.
First of all, Professor Qiu Zhigang used the "Double Eleven" case as an entry point to talk about the impact of big data: small, medium and micro enterprises and individuals have little financial transaction data and have enjoyed relatively few financial services in the past. The development of third-party payment integrates and utilizes data that has appeared but has not been recorded, so that financial services in the big data era can cover small, medium and micro enterprises and individuals. The development of big data is also promoting the progress of science and technology, such as cloud computing, edge computing, federated learning, knowledge graph, etc. These technologies can process data without touching the core and are technologies "derived from data".
Next, Professor Qiu Zhigang introduced the relevant knowledge of financial risks through a detailed analysis of the P2P (peer to peer) model. Professor Qiu Zhigang introduced the concept and main risk characteristics of P2P platforms, pointing out that more than 90% of platforms on the market do not meet the definition of the P2P model.
The first relevant case is Ezubao. Ezubao establishes basic claims for financial leasing through manufacturers, obtains predictable and stable cash flow, and sells it to the public in the form of Ezubao, a financial management product. Professor Qiu Zhigang pointed out that this model is actually an A2P operation model. During its operation, Ezubao has no third-party guarantee agency and lacks supervision. When a large amount of cash pours in, far exceeding the demand for leasing business, the platform chooses to take risks to find high-return investment opportunities, which also brings high risks.
The second relevant case is Rijinbao. Rijinbao, a subsidiary of Pan Asia, was once promoted as an investment attraction project in Kunming City, Yunnan Province. The real economy it relied on was nonferrous metal trading. However, the scale of non-ferrous metal transactions is small and the demand from buyers is limited. Eventually the project collapsed and turned into a Ponzi scheme.
Based on the above cases, Professor Qiu Zhigang believes that the fundamental problem of the P2P model comes from: the foundation of finance is the real economy, and the free funds of fund demanders must be greater than a certain minimum critical value. Due to information asymmetry, financing is simply impossible without basic collateral, that is, true unsecured loans do not exist.
Professor Qiu Zhigang used the model to specifically analyze big data lending and financial risks. In the operation of "P2P" platforms, bank intervention can control risks to a certain extent, but the role of bank supervision is limited. Another way is to start from the real economy, increase product quality and reduce moral hazard.
Big data provides signals, trading volume increases, and capital supply increases. The media and expert platforms act as "collateral", and together with financial repression, stimulate the influx of large amounts of funds into P2P platforms. Direct financing cannot solve information asymmetry. This direct lending relationship bears the risk on the platform itself and is still a high-risk, high-yield transaction; P2P is not an innovation, but the big data financial model represents financial innovation. Let the students deeply realize that as practitioners in the financial industry, they should not forget their original intentions and should not let the people's trust become collateral.
Finally, Professor Qiu Zhigang shared his in-depth thinking on financial risks and technology, and raised a series of valuable issues from multiple perspectives. Data mining - fundamental analysis to analyze the information behind the data, whether it is reasonable to reflect price discrimination, whether data noise, which is worthless data in the traditional data era, is used, whether big data can make more accurate judgments, whether art patents and data ownership can be determined with the help of blockchain technology, whether digital inclusive finance can be fully developed in the data era, and other issues that the development of the data economy is facing in real life, triggering students to further discuss and think about financial risks and technology.
