# 🏦 Bank Churn Analysis

# Business Problem

# 

# A retail bank wants to understand why customers leave and identify the factors contributing to customer churn.

# 

# Objectives

# Analyze customer churn behavior

# Identify high-risk customer segments

# Compare churn across countries

# Evaluate customer demographics

# Recommend strategies to improve retention

# Dataset

# 10,000 Customers

# Banking Industry

# Customer Demographics

# Financial Information

# Account Activity

# Dashboard Preview

# 

# KPIs

# Total Customers

# Churn Rate

# Active Customers

# Average Balance

# Average Credit Score

# Key Insights

# Germany recorded the highest churn rate.

# Older customers were more likely to churn.

# Inactive members showed significantly higher churn.

# Customers with higher balances exhibited greater churn risk.

# Recommendations

# Improve engagement for inactive customers.

# Launch retention campaigns for high-risk segments.

# Strengthen loyalty programs for long-term customers.

# Develop personalized offers based on customer profiles.

# Skills Demonstrated

# Power BI

# Power Query

# DAX

# Data Modeling

# Dashboard Design

# KPI Development

# Business Storytelling