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This repository uses a Kaggle dataset for a classification task: determining if bank clients are likely to invest in long-term deposits. Aimed at assisting banks with revenue declines, it targets customer classification, optimizing marketing efforts towards potential long-term depositors.

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danielbitonn/bank_clients_classification

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bank_clients_classification

Banking Dataset Classification

Introduction

There has been a revenue decline in the Portuguese Bank and they would like to know what actions to take. After investigation, they found that the root cause was that their customers are not investing enough for long term deposits. So the bank would like to identify existing customers that have a higher chance to subscribe for a long term deposit and focus marketing efforts on such

Business Motivation

There has been a revenue decline in some banks, and they would like to know what actions to take.

After investigation, they found that the root cause was that their customers were not investing enough for long-term deposits.

Target and Success definition

The marketing campaigns required high costs and much effort based on phone calls. More than one contact with the same client was often necessary to verify if a long-term deposit is relevant and if the customer will invest in ('yes' or 'no').

Therefore the bank would like to identify existing customers that have a higher chance of subscribing to a long-term deposit base on their internal data and focus marketing efforts on such.

The Target is to classify a customer who would be ('YES' or 'NO') a subscriber of a long-term deposit investment based on his banking data.

*Including a new customer

About

This repository uses a Kaggle dataset for a classification task: determining if bank clients are likely to invest in long-term deposits. Aimed at assisting banks with revenue declines, it targets customer classification, optimizing marketing efforts towards potential long-term depositors.

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