首页 /研究 /The Use of Artificial Intelligence in Banking Industry
LEARNING

The Use of Artificial Intelligence in Banking Industry

Reza Farishy

发表年份
2023
引用次数
12
访问权限
开放获取

摘要

Industry 4.0, also known as the fourth industrial revolution, has altered society and the economy by introducing intelligent robotics, artificial intelligence (AI), cloud computing enormous data sets, the Internet of Things (IoT), and 3D printers, among other scientific advances. To maintain competitiveness and keep up with global competition, it is vital to adapt to modern technology. The financial sector is a vibrant market with intense competition for products and services, and advancements in information technology have led to the development of highly valuable new technologies. This essay addresses the possible advantages of artificial intelligence in the banking sector. The study utilized a Systematic Literature Review (SLR) to evaluate the current literature on AI in the banking industry. The results of the SLR demonstrate that AI has been utilized in the banking industry in a variety of ways, including credit rating models and bank collapse prediction. In establishing credit card eligibility, logistic regression models were shown to be effective, with an accuracy rate of 80.43 percent. With a precision rate of 75.7% and a recall rate of 75.7%, artificial neural networks (ANNs) were shown to be the most accurate method for predicting bank collapse based on financial characteristics. Overall, the study indicates that AI has the ability to dramatically improve the banking business by enhancing efficiency, precision, and decision-making procedures. The study has limitations and potential biases, including the exclusion of non-English language articles and the possibility of a selection bias. To explore the full potential of AI in the banking business, additional study is required.

关键词

Competition (biology)Artificial intelligenceBig dataFinancial servicesComputer scienceCredit cardCloud computingMachine learningBusinessFinance

相关论文

查看 LEARNING 分类全部论文