https://github.com/amoshnin/ml-customer.churn.prediction

My machine learning pet project on Customer Churn Prediction Analysis using Ensemble Techniques
https://github.com/amoshnin/ml-customer.churn.prediction

Last synced: about 5 hours ago
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My machine learning pet project on Customer Churn Prediction Analysis using Ensemble Techniques

• Host: GitHub
• URL: https://github.com/amoshnin/ml-customer.churn.prediction
• Owner: amoshnin
• Created: 2022-06-17T13:50:30.000Z (over 2 years ago)
• Default Branch: master
• Last Pushed: 2023-10-03T12:02:26.000Z (about 1 year ago)
• Last Synced: 2024-05-21T05:56:37.315Z (6 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 13.4 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## Bank Customer Churn Prediction Machine Learning Model

#### By Artem Moshnin

### Problem description

- Some well-known bank has been observing a lot of customers closing their accounts or switching to competitor banks over the past couple of quarters.

- This has caused a huge dent in their quarterly revenues and might drastically affect annual revenues for the ongoing financial year, causing stocks to plunge and market cap to reduce significantly.

- The idea is to be able to predict which customers are going to churn so that necessary actions/interventions can be taken by the bank to retain such customers.

### Problem description from data science perspective

- To develop a solution for this churn prediction problem I have been using customer data pertaining to his past transactions with the bank and some demographic information.

- I have used this customer data to establish relations/associations between data features & customers' propensity to churn by building a classification model to predict whether the customer will leave the bank or not.

- Furthermore, with an objective of explaning model predictions, I have built multiple visualisations which give insight into which factors are responsible for the churn of the customers.