Huimin ZhuXiaoBin

【Abstract】This paper aims to search AI technology in banking management from the angle of customer support， digitization， aids regulatory compliance， blockchain， ?improving decision-making for loans and credit， reducing bank operating costs and risk， the big data problem， AI based technological applications by Indian banks， impact of MIT research in AI and Librarians and Big Data. Empirical conclusion found possibilities of AI-assisted research. In conclusion， AI will play an important role in future banking management.

【Key words】AI technology; appliance; banking; management; assistance

【作者簡介】Huimin Zhu， Xiao Bin， Chanchai Bunchapattanasakda， Shinawatra University， Thailand Beijing Institute of Petrochemical Technology.

The use of artificial intelligence （AI） is revolutionizing our research in science and technology inefficiency. AI increases availability for life science and healthcare information， retailing， banking， travelling and other sectors（Reed， Jaze Z.， 2018）. AI is also used to search bank data for signs of unusual behavior， including ?banking fraud and the sale of software.

After 2012， thanks to the increase of data volume， the improvement of computing power and the emergence of new algorithm of machine learning， artificial intelligence develops rapidly in industrial application. The development and application of AI in enterprise management play an increasingly important role.

1. Applications of AI in Banking Management

AI technology improves human intelligence and life style with advanced clarity of skills and vast volume of knowledge deposit. Initiating common sense， reasoning and problem-solving power in machines is a difficult and tedious task while AI is good at. Besides， Machine learning is also AIs core part， in which machine perception deals with the capability to use sensory inputs to deduce the different aspects of the world， while computer vision is the power to analyze visual inputs with a few sub-problems such as facial， object and gesture recognition. Robotics is also a major field related to AI. Robots require intelligence to handle tasks such as object manipulation and navigation， along with sub-problems of localization， motion planning and mapping. （Marks， Paul， 2012）

1.1 Customer Support

Web robots or internet bots are programmed to process automated tasks. Such services will bring customers sense of happiness， avoiding waiting lines in the bank in the near future.

Research finds that the 233-year-old financial institution is banking on “bots，” specifically robotic process automation （RPA）， to improve the efficiency of its operations and to reduce costs.

BNY Mellon reports that the implementation of RPA has led to the following results：100 percent accuracy in account-closure validations across five systems， 88 percent improvement in processing time， 66 percent improvement in trade entry turnaround time， ?-second robotic reconciliation of a failed trade vs. 5-10 minutes by a human.

1.2 Digitization

Artificial Intelligence applied in digitization for simplified banking experiences and enhanced productivity. According to the research done by ProSchool， AI digitization created a comprehensive platform . AI serves as conversational assistants， or chatbots， bank transactions， bank services and other tasks that don?t necessarily require human intervention， to engage customers twenty-four hours for seven days a week. In addition to fielding customer service inquiries and conversations about individual transactions， banks have been finding good results using chatbots to make their customers aware of additional services and offerings in helping ?resolve payment or credit issues on the bank site or mobile application website.

1.3 AI Aids Regulatory Compliance

Banking regulatory compliance has a significant cost and even higher liability. As a result， banks are looking to smart， always-on AI assistants to monitor transactions， keep an eye on customer behaviors， and audit and log information for various compliance and regulatory systems. Big data-enhanced fraud prevention， by looking at customer behaviors and patterns instead of specific rules， AI-based systems can assist banks stay on top of regulatory compliance while minimizing overall risk.

1.4 Blockchain

Now customers purchasing habits are undergoing a great change both in purchasing products and payment styles. Blockchain is established to implant the advantage of the payment process to speeds up the procedure of payment through enhancing assistance and satisfaction.

Report from the Institute of Chartered Accountants of India （ICAI） has announced its plans to re-skill around 1.2 lakh of its members in disruptive technologies such as Data Analytics， Artificial Intelligence and Blockchain. It is believed to be a praiseworthy move to impact auditing and accounting greatly and the members need to be prepared for these emerging trends by the institute. （Ayushman Baruah，2018）

1.5 AI in Improving Decision-Making for Loans and Credit

AI can now personalize the financial services in helping customers make better financial decisions through automated financial planners and advisors in purchasing stocks and bonds after analyzing Rethe market structure against the users financial purposes. Currently， many banks are still confined to the use of credit reporting system to determine an individual or company credit worthy.

Due to these imperfect credit system， AI-based loan decision loan decision system and credit decision has been explored models of machine learning and deep learning approaches.

1.6 ?Reducing Bank Operating Costs and Risk

The worlds bank industry is largely digital in operation， but still with human-based processes. AI in banking is being applied to these processes to eliminate much of the time-intensive and error-prone work. By improved handwriting recognition， natural language processing and other technologies， being combined with intelligent process automation tools， AI are being used more and more in back-office operations to handle a wide range of banking workflows.

By replacing humans with intelligent， automated assistants， banks can focus their human resources on higher-value tasks， such as offering new services to their customers or improving customer satisfaction. According to Accenture， banks are seeing between 20-25% savings in their operations by implementing intelligent assistants and AI-based systems into their back-office workflows.

1.7 Big Data

Big Data， referred to as the collection of massive amounts of data from myriad formats， now means “Internet of Things”， or data collected from deliberately placed sensors located everywhere， concerning with every aspects on human beings. Now， AI is the trendy term as the algorithm or computer code that manipulated this collected data and combines it with machine learning to answer questions and try to solve problems in recent research application in weather broadcasting and television meteorology， medical services like CT scans， perusing legal documents and flag non-standardized language.

2. Empirical Cases

The implementation of AI by the seven leading commercial banks in the U.S. as ranked by the Federal Reserve is also undertaking according to Tech emergence report， starting with JPMorgan Chase， the largest.

Wells Fargo announced the establishment of a new Artificial Intelligence Enterprise Solutions team in February with Steve Ellis， EVP as head of the companys Innovation Group， nestled under the umbrella of the Payments， Virtual Solutions and Innovation group.（Kumba Sennaar， 2018）

Bank of ?NY Mellon Corp. announced that over the past 15 months the company has rolled out more than 220 bots developed by Blue Prism for handling tasks that are often repetitive in nature and normally handled by staff.

3. Prospect of AI

AI ?is poised to transform every industry， ?just as electricity did 100 years ago. It will create $13 trillion of GDP growth by 2030， according to McKinsey， most of which will be in non-internet sectors including manufacturing， agriculture， energy， logistics， and education. ?The rise of AI presents an opportunity for executives in every industry to differentiate and defend their businesses. But implementing a company-wide AI strategy is challenging， especially for legacy enterprises. （Andrew Ng，2019）

AI ?is driving the engine of innovations and transforming the way customers assisted. It is working on providing personalized support， high-quality customer experience， speed with efficiency and cost saving services.

In all these ways， AI in banking is continuing to transform the industry to provide a greater level of value to their customers， reduce risks， and increase opportunities as the financial engines of our modern economy.

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