Introduction to the Application of Artificial Intelligence Technology in Financial Industry

The first AI-driven fund, Rebellion, successfully predicted the stock market crash in 2008 and rated Greek bonds F in 2009, while Fitch still ranked A. Through AI, Rebellion was one month ahead of the official downgrade; Cerebellum, a $90 billion hedge fund, used AI technology from 20. It has been profitable since 2009.

In China, Ant Golden Garment has successfully applied AI to the fields of Internet lending, insurance, credit information, asset allocation and customer service; Zhirong Golden Garment has achieved more than 200,000 loans per month by using AI wind control system, and the speed of conventional machine auditing takes only 8 seconds; China Merchants Bank's visual counter and the AI machine launched by Bank of Communications call "Jiao Jiao Jiao Jiao" and so on. In the field of intelligent customer service has made an early attempt and exploration.

In companies invested in innovative workplaces, the fourth paradigm of machine learning excels in precision marketing, asset forecasting, risk prevention and control in banking industry, and the worldwide technology of machine vision (the main product is Face++) provides advanced solutions for traditional finance and Internet finance, such as identity verification, intelligent access control, employee attendance, etc. The Qianbao Company, which mainly operates on the Internet micro-credit platform, has established a high-quality wind control model by using artificial intelligence technology, which greatly improves the passing rate of credit business, reduces the bad debt rate and achieves astonishing performance growth.

Take Qianbao as an example, the company's main mobile app was launched only in July 2015. In just one and a half years, by December 2016, the number of monthly transactions with Qianbao app had exceeded 10 million. This growth rate is very striking in financial mobile applications. There is only one key secret for Qianbao to grow rapidly under the condition of controllable risk. Machine learning technology is used to automatically analyze data containing a large number of strong and weak features, and to automatically judge and trade risks.

Traditional credit wind control often uses a mathematical model called "risk scoring card", which relies on a large number of strong features in the form of non-zero or one to calculate a customer's risk level. Such a traditional mathematical model considers few factors, and it is very simple to fit the real risk. It is difficult to migrate directly to the Internet financial customers with weak characteristics.

If a person's data is compared to an iceberg, then strong feature data is only the tip of the iceberg, and there are a large number of weak feature data, such as e-commerce data, equipment data, location data, behavior data, etc. At the same time, as the mother of all industries, there is a huge interwoven network between the financial industry and the whole society, which precipitates a large number of useful or useless data, including various types of financial transactions, customer information, market analysis, risk control, investment consultants and so on. These data units are massive, and a large number of data exist in an unstructured way, which can not be converted into data that can be effectively analyzed by traditional models.

What AI algorithms represented by in-depth learning need to do is to fully tap and effectively utilize these massive weak feature data and establish a more realistic mathematical model. Although it is impossible to make loan decisions based on a few of these data, if we combine hundreds or even thousands of dimensions of data, we can train an effective wind control model and make loan decisions for users on the basis of wind control.

Driven by artificial intelligence technology, new financial applications such as Qianbao can greatly reduce labor, improve efficiency and reduce costs. Future financial technology will be an organic combination of the Internet and AI, and the resulting intelligent financial services will become an important part of everyone's life.

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Author: Duozhishidai

Source: CSDN

Original: https://blog.csdn.net/duozhishidai/article/details/89397558

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