Client behavior prediction with AI model in Banking
Learn how to predict client behavior in the banking industry using AI models. Discover techniques for analyzing customer data to make accurate predictions and improve decision-making processes.
At a Glance
The purpose of this laboratory is to develop different types of classifiers of artificial intelligence and their ensembles for the classification of customers in banking.
The purpose of this laboratory is to develop different types of classifiers of artificial intelligence and their ensembles for the classification of customers in banking.
During the work, the task of a preliminary analysis of a positive response (term deposit) to direct calls from the bank is solved. In essence, the task is the matter of bank scoring, i.e. according to the characteristics of clients (potential clients), their behavior is predicted (loan default, a wish to open a deposit, etc.).
During the work, the task of a preliminary analysis of a positive response (term deposit) to direct calls from the bank is solved. In essence, the task is the matter of bank scoring, i.e. according to the characteristics of clients (potential clients), their behavior is predicted (loan default, a wish to open a deposit, etc.).
What you will learn
After completing this lab, you will be able to:
- compare different types of classifiers
- create an ensemble of models
- create an ensemble of classifiers based on neural networks
- classify clients on the basis of developed models
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