Financial Innovation in the Age of Data – Interview with WANG Hai, A Famous Expert in Financial Analysis in China

September 22 17:57 2021

Financial market is a game platform with many participants, and analyzing the situation is a crucial step in financial activities. WANG Hai is a well-known analysis expert in China’s financial industry, specializing in all-round analysis of financial environment, financial products and trends. Relying on the theoretical and technical achievements of independent innovation, she has made reasonable and scientific decision-making recommendations for many customers to ensure their effective investment, enhance the return on investment and promote the industry’s sound and fast development.

Innovative Analysis Methods Based on Data Mining

In recent years, with the continuous development of technology, various industries have started to establish databases on a large scale, and huge amounts of data information have exploded in people’s work and life. A large amount of useful information is hidden in these databases, and traditional manual reading or data retrieval methods cannot effectively extract them from different levels of information, resulting in a serious waste of data and information resources, and cannot meet the current data application needs. The financial industry is also troubled by this problem, and inefficient data and information integration leads to missed opportunities for related financial institutions, which greatly reduces economic benefits. As an authoritative analysis expert in the financial industry in China, WANG Hai introduced data mining technology into the field of financial analysis and achieved excellent application results.

She believes that the scientific, accurate, and rigorous advantages of data mining technology can discover the inner meaning of financial information in a deeper way. Therefore, she adopted mathematical statistics, regression analysis and classification and clustering methods in data mining to quickly analyze data information and automatically and intelligently transform massive financial data into useful financial knowledge, providing a large amount of information reference for the formulation of future development decisions in the financial industry and making the future development strategies of financial industry-related enterprises more effective and scientific. On this basis, WANG Hai summarized the methods of financial information analysis based on data mining technology, and proposed a variety of financial information analysis methods including classification method, clustering method, regression analysis method, association rule method, neural network method, etc., which not only improve the investment and financing ability of relevant enterprises, but also make the financial industry structure and management methods upgrade and innovate, providing a broader space for the development of the financial industry.

Relying on Information Technology To Develop Analysis Systems

In addition to innovation in theoretical methods, she also has made outstanding achievements in technological innovation. In recent years, relying on solid professional skills and rich practical experience, she has innovatively applied big data, blockchain, artificial intelligence and other technologies to financial analysis with the goal of improving asset returns, and has developed numerous technological achievements with advanced core technologies and significant application results, including “Financial Data Analysis System of Supply Chain Based on Blockchain”, “Supply Chain Trade Finance Risk Assessment Platform Based on Three-Stream Model”, “Retrieval and Classification System for Similar Listed Companies Based on Artificial Intelligence Algorithms”, etc., which effectively solved the technical problems of the industry, improved the efficiency of financial services, and driven the healthy, efficient and intelligent development of the financial industry while avoiding financial risks and improving customer returns.

For example, the “Retrieval and Classification System for Similar Listed Companies Based on Artificial Intelligence Algorithms” developed by WANG Hai has effectively filled the gap in the search and analysis technology for benchmark companies in the financial industry. In the field of financial investment, investors need to find benchmark companies for relevant business, financial and value analysis. The traditional approach is mostly based on text search, such as collecting prospectuses, annual reports, important announcements, industry research reports, patent information, tendering and bidding information and important corporate news of listed companies. Using text analysis and retrieval, knowledge base reasoning, keyword extraction and other technologies to classify companies’ similarity, these methods have not really touched the core data of listed companies—financial data, and the collected information has incomplete coverage, poor practicability and inaccurate data. In response to the above problems, WANG Hai independently developed “Retrieval and Classification System for Similar Listed Companies Based on Artificial Intelligence Algorithms”, which can obtain the annual financial statements of benchmarked enterprises, combine the current mainstream machine learning algorithms to build an artificial intelligence model, and give detailed data reports through extraction, calculation and analysis, effectively solving the problems of incomplete coverage of traditional data and inaccurate data and low practicality of traditional enterprise search system.

Original Achievements Serve the Financial Market

WANG Hai always believes that the transformation of scientific and technological achievements is the key to innovation, and a technological achievement that cannot be applied to the market is an invalid innovation. Therefore, she not only focuses on the innovation of theoretical methods and technological achievements, but attaches great importance to the transformation of achievements. Over the past years, she has vigorously promoted her self-developed technological achievements and theoretical methods, helping more than 1,000 enterprises nationwide create considerable economic benefits, and has been highly recognized and praised by the industry.

In banking services, WANG Hai uses her original technological achievements to help banks develop relevant lending strategies and carry out lending work in a scientific and efficient manner. Banks have a wide range of lending operations, and loan repayment and customer credit rating evaluation are affected by many factors, including loan interest rates, loan terms, the income level, education and repayment level of lenders, etc. Therefore, a large amount of data poses a huge challenge to the banks’ credit collection efforts. WANG Hai uses self-developed technological achievements and theoretical methods to completely eliminate irrelevant factors from the data and carry out loan repayment predictions based on customer information, through which banks can develop appropriate lending strategies. With the help of WANG Hai, the bank not only reduced loan losses, but also maximized economic benefits.

In the financial investment services, WANG Hai has provided technical support for many financial institutions, enabling the relevant financial institutions to better carry out their targeted business work and enhance their economic returns. In June 2019, a well-known fund company in Shanghai had to carry out targeted service work for 500 potential customers. In the traditional way, the company would communicate with customers through social tools such as phone and WeChat to understand the specific ideas of these 500 customers one by one, but this not only wasted time and reduced work efficiency, but failed to accurately make product recommendations for customers. As a result, WANG Hai adopted her original technological achievements to build a customer asset activity analysis system for the company. Through the analysis of their past investment behavior, effective customers are accurately extracted and classified, and the targeted business introductions are made according to their preferences, enabling customers to have a concrete understanding of relevant business activities while significantly improving the company’s work efficiency.

Reporter: LIU Tao

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