At the core of the Fourth Industrial Revolution are new technological innovations in six areas: big data analytics, artificial intelligence, robotics, the Internet of Things, unmanned vehicles, three-dimensional printing, and nanotechnology.
As a result, the domestic financial environment is cha...
At the core of the Fourth Industrial Revolution are new technological innovations in six areas: big data analytics, artificial intelligence, robotics, the Internet of Things, unmanned vehicles, three-dimensional printing, and nanotechnology.
As a result, the domestic financial environment is changing rapidly. Competitiveness among financial institutions is intensifying by proposing digital electronic banking regulation as a new paradigm. Intensifying competition and the development of information technology have established large-scale databases to create corporate customers, competitors, and new business models. Efforts to effectively analyze and informatize large amounts of data for efficient decision making are increasing.
Customers have become picky and raising their eye level by offering various products and services from many different kind of companies.
Customers dissatisfaction and abandonment their main bank or company would negatively affect company’s financial performance. so it will be a key point for future management strategies by managing customer satisfaction to attract existing customers and attract new customers.
Recently, we have applied the method of quantifying deep learning-based customer's activity type using the artificial intelligence technique used in big data research field into measurable variables. Therefore, it is needed for effective and practical survival strategy to overcome these changes.
In this study, the optimal model evaluation was performed by analyzing the results of each methodology of logistic regression, decision tree, and neural networks. However, although the consistency of the prediction model is excellent, it is difficult to analyze the causal relationship of the cause. To compensate for this, the results of the cause were analyzed through the autoencoder, an unsupervised learning model. In addition, the financial impact of the company due to customer churn is described based on metric indicators.
At the core of the Fourth Industrial Revolution are new technological innovations in six areas: big data analytics, artificial intelligence, robotics, the Internet of Things, unmanned vehicles, three-dimensional printing, and nanotechnology.
As a result, the domestic financial environment is changing rapidly. Competitiveness among financial institutions is intensifying by proposing digital electronic banking regulation as a new paradigm. Intensifying competition and the development of information technology have established large-scale databases to create corporate customers, competitors, and new business models. Efforts to effectively analyze and informatize large amounts of data for efficient decision making are increasing.
Customers have become picky and raising their eye level by offering various products and services from many different kind of companies.
Customers dissatisfaction and abandonment their main bank or company would negatively affect company’s financial performance. so it will be a key point for future management strategies by managing customer satisfaction to attract existing customers and attract new customers.
Recently, we have applied the method of quantifying deep learning-based customer's activity type using the artificial intelligence technique used in big data research field into measurable variables. Therefore, it is needed for effective and practical survival strategy to overcome these changes.
In this study, the optimal model evaluation was performed by analyzing the results of each methodology of logistic regression, decision tree, and neural networks. However, although the consistency of the prediction model is excellent, it is difficult to analyze the causal relationship of the cause. To compensate for this, the results of the cause were analyzed through the autoencoder, an unsupervised learning model. In addition, the financial impact of the company due to customer churn is described based on metric indicators.
주제어
#Deep Learning Customer Leakage Prediction of Defection Data Mining Logistic Regression Decision Tree Neural Networks AutoEncoder Financial Performance
※ AI-Helper는 부적절한 답변을 할 수 있습니다.