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下面为大家整理一篇优秀的paper代写范文- The application of artificial intelligence in the financial field，供大家参考学习，这篇论文讨论了人工智能在金融领域的应用。互联网金融的兴起，让计算机视觉、自然语音处理、机器人、语音识别等人工智能技术在金融行业中得到了广泛的应用。在互联网金融中使用人工智能技术，及极大地提高了互联网金融的效率。

Artificial intelligence is a new technology science that develops the theories, methods, technologies and application systems of human intelligence for simulating, extending and extending human intelligence. Artificial intelligence has been mentioned as early as 1956. With the innovation of computing methods, the improvement of hardware level and the common drive of cloud computing big data in recent decades, artificial intelligence has been widely concerned and studied by various industries. In particular, in 2016, Google's Alpha Go defeated lee sedol, and then the Alpha Go upgraded Master continued to challenge the top human Go masters, maintaining the undefeated record of 60 matches, making artificial intelligence famous for a while.

According to the 2017 China artificial intelligence industry report released by iresearch, the scale of China's artificial intelligence industry reached 10.06 billion yuan in 2016 with a growth rate of 43.3%. It is expected to reach 15.21 billion yuan in 2017 and increase to 34.43 billion yuan in 2019.

Differentiated services in the financial industry have always been based on "people". In recent years, however, robots have emerged to mimic human functions to some extent, and mass and more personalized services are trying to take their place. With the rise of Internet finance, computer vision, natural speech processing, robotics, speech recognition and other artificial intelligence technologies have been widely used in the financial industry. At the second China fintech conference, baidu senior vice President zhu guang pointed out that finance is the best landing scenario for artificial intelligence, because its core lies in data and data processing.

From traditional finance to "Internet + finance", whether it is traditional credit approval or collection of Internet products, such as P2P and cash loan, risk prevention and control has always been an important topic for banking financial institutions. In the past, the identification, monitoring and feedback of the lender before the loan, during the loan and after the loan were generally based on the field investigation of a large number of credit staff, which greatly increased the one-sidedness and error of credit risk assessment. At present, with the help of artificial intelligence and big data to collect and authenticate customer information. The multi-channel and multi-dimensional acquisition of customer information data and the realization of intelligent credit investigation and approval can greatly accelerate the speed of bank credit and limit incremental risks and reduce information asymmetry. In the traditional bank credit risk control model, the variables cover only 20 ~ 30, while the intelligent risk control system model based on user data accumulation and artificial intelligence technology can exceed 10,000 units. Several institutions, including the Australian securities and investment commission, the monetary authority of Singapore and the securities and exchange commission of the us, have introduced AI to risk management.

In the bank customer service, the user's consultation question has the repetitive characteristic. Ai USES the deep learning system to collect customer data from the front end, such as user information and behavior dynamics, and then carries out multi-dimensional and standardized marketing by combining customer gender, age and hobbies. First, Banks are replacing lobby managers with high-tech, interactive robots to improve customer experience and reduce costs. For example, bank of communications' "jiaojiao", China minsheng bank's "ONE" and agricultural bank of China's "smart little talent". Secondly, in recent years, China construction bank, bank of China and other Banks have successively established "smart Banks", subverting the traditional banking model. Customers will handle various businesses under the guidance of intelligent robots to enhance the sense of technology and service experience of the bank.

Compared with traditional investment advisers, intelligent advisers can provide faster, more reliable, more objective and more reliable investment schemes by using collected economic data through machine learning and neural network technology, through data analysis and processing, construction and improvement of models. At the same time, artificial intelligence can also collect data, conduct data analysis, and automatically write various reports. For example, prospectuses, industry research reports, due diligence reports and term sheets. Ken sho, a forerunner of investment advisors, is able to judge in two minutes based on historical data the trend of the standard & poor's and dow Jones indexes over the years before the federal reserve raised interest rates, and judge the positive industry and potential companies, which was hard to achieve in the past days and nights relying on human analysts. According to data from citibank, from 2012 to the end of 2015, the assets under the management of intelligent advisers have grown from 0 to 29 billion dollars, and will reach 5 trillion dollars in the future. The artificial intelligence system of Beijing apaiyi investment consulting company can judge the buying and selling time and position size according to the market signal. In addition, there are jd financial at home and abroad to launch the wisdom of investment, small gold by the robot investment adviser. In the second half of 2016, blackrock, the world's largest asset management company, spent $150 million to $200 million to acquire the financial management startup "future advisor" and the robot client "Anlage Finder" launched by deutsche bank.

In recent years, with the development and application of big data, cloud computing, artificial intelligence and other new technologies, the insurance industry has entered a more efficient and faster era. First of all, in the traditional insurance industry, how to store a large number of paper or video policies, certificates, notes and other data is a big problem for insurance companies. According to statistics, the annual labor cost of a data entry team of 100 people ranges from 2 million yuan to 6 million yuan. However, by participating in big data and deep algorithms, AI can save 90% of the storage space after data construction. Secondly, how to transfer, search and analyze the stored data is becoming more and more important. Artificial intelligence, through data accumulation and algorithm iteration, can provide accurate data for the pricing of insurance companies' products. At the same time, through machine identification to participate in insurance claims, can reduce the risk. At present, a number of domestic and foreign insurance companies have begun to layout artificial intelligence. For example, taikang life insurance intelligent robot "TKer", ping an life insurance "intelligent robot", united life insurance artificial intelligence "small Ai", Pacific insurance intelligent operation and maintenance robot, hong kang life insurance introduced "face recognition technology", Japan fuguo life insurance artificial intelligence platform "Watson Explorer", Taiwan cathay life "Pepper" and so on.

As a supplement to traditional finance, Internet finance provides business activities such as financing, payment and settlement through relying on Internet technologies and tools. At present, the development of China's Internet finance has gone through two stages. At the initial stage, Internet finance only provides network services for traditional financial businesses, that is, to move financial products such as insurance, financial management, fund and trust to the Internet for marketing. Now, Internet finance covers a variety of models such as third-party payment, P2P online lending, big data finance, crowdfunding and third-party financial service platforms. First, artificial intelligence improves the efficiency of Internet finance. Intelligent customer service can be realized through an automatic question-answering robot. During the "double 11" in the past two years, 95% of ant financial's customer service is completed by the intelligent robot through remote customer service, business consulting and handling through voice recognition. Second, with the guiding opinions on promoting the healthy development of the Internet "non-banking institutions network payment business management method" and "the supreme people's court on some issues of applicable law in private lending cases regulations and a series of policies, it is not difficult to found that Internet financial risk in financial advisers, credit reporting assistant, intelligent control and guard against risk in the financial system has been gradually standardized and legalized. For example, for a long time, due to the lack of effective management, information security, risk control, capital regulation and other issues are increasingly prominent. In December 2016 alone, there were 69 "runaway" platforms, according to the 2016 national P2P online loan industry express. The emergence of artificial intelligence can effectively regulate and avoid risks. Online Banks have reduced fake credit transactions by 10 times in their huabai and microcredit businesses, according to alibaba's ant financial. Using OCR system, alipay certificate approval from 1 day to 1 second. Baidu USES big data and artificial intelligence to achieve education credit second batch.

In addition to the above mentioned artificial intelligence is used in the financial industry for credit assessment, customer service, market research, prediction analysis, insurance. In addition to the U offer, ai is also used in loan collection, corporate finance and expense reporting.

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