Decoding Bank Customer Churn: Insights through Data Analysis"

Have you ever wondered what causes a bank to lose its customers?

here's an analytical solution provided on what causes an company to lose its customers.

I'm Pavan kalyan, and I'm thrilled to welcome you to my data science blog. As an aspiring data scientist, I have always been fascinated by the power of data to uncover meaningful insights and drive informed decision-making. With a background in data science, I am passionate about leveraging data science techniques to solve real-world problems. 

The purpose of this blog is to share my journey in data science and provide a detailed analysis of a fascinating project: bank customer churn.

In today's competitive landscape, retaining customers is crucial for the success of any business, and banks are no exception. Customer churn, or the rate at which customers leave a service or product provider, is a significant concern for banks worldwide. By understanding the factors that contribute to customer churn, banks can implement targeted strategies to retain customers and improve overall profitability.

Introduction to the topic

Bank customer churn refers to the phenomenon where customers stop doing business with a bank, either by closing their accounts or reducing their engagement with the bank's services. In simpler terms, it's like when customers "leave" the bank.

Now, you might wonder why customers decide to leave their bank. Well, there may be several reasons behind it. We are going to play with the data and answer the 10 most critical questions.

1. What is the distribution of churned and non churned of bank customers?
2. What is the age distribution of the data?
3. what is the gender distribution of the data?
4. How does customer age influence their account balance?
5. What is the distribution of credit scores among bank customers?
6. How does customer churn vary across different geographical regions?
7. Is there a significant difference in churn rates between genders?
8. What is the average age of customers who churned compared to those who stayed?
9. Does tenure with the bank impact the likelihood of churn?
10.What is the distribution of account balances among customers who churned?
11.How does the number of products held by a customer relate to churn?
12.Does customer activity (e.g., logins, transactions) affect churn rates?
13.What is the satisfaction score distribution among customers who churned?
14.Relationship among churned and complain

To shed light on this pressing issue, we embark on a journey of exploration and analysis, aiming to uncover the factors contributing to customer churn in the banking industry.

Data collection: The dataset was sourced from Kaggle, a popular platform for accessing and sharing datasets. This dataset was chosen for its relevance to the analysis objective, which focused on understanding customer churn in the banking industry.

Data Preprocessing: Before conducting any analysis, it was imperative to preprocess the dataset to ensure its quality and reliability. During the data preprocessing phase, thorough checks were conducted to identify any duplicates, outliers and missing values in the dataset. Despite the comprehensive review, no such anomalies were found, indicating the dataset's high quality and reliability for analysis purposes.

lets perform the EDA to answer the questions.

Question 1: What is the distribution of churned and non churned of bank customers?

In our dataset, it's evident that the churn rate exceeds 2000 customers, whereas the count of non-churned customers stands at around 8000. This difference highlights a concerning trend, the bank is experiencing a significant loss of customers.

Question 2: What is the age distribution of the data?

The age range of customers engaging with the bank spans from 20 to 90 years old. Interestingly, the age group of 30 to 40 years old appears to be the most prevalent among the bank. Conversely, there is a decline in customer numbers within the 70 to 90 age range. This observation suggests that the bank may need to tailor its offerings to better cater to the needs of customers across different age groups.

Question 3: what is the gender distribution of the data?

The data suggests that both male and female customers are actively engaged with the bank. However, it's notable that there is a slightly higher representation of male customers in the dataset. This implies that the bank may have a larger customer base comprising males, potentially indicating a higher volume of business done by males.

Question 4: How does customer age influence their account balance?

The analysis reveals that customers between the ages of 25 to 50 maintain higher account balances, indicating their significant contribution to the bank's financial flow. This insight suggests that the bank can tailor its strategies to attract and retain customers within this age group.

Question 5: What is the distribution of credit scores among bank customers?

We noticed that customers' credit scores range widely, from as low as 300 to as high as 800 or more. This means the bank may be more willing to approve loans for those with higher credit scores.

Question 6: How does customer churn vary across different geographical regions?

The analysis reveals that France and Germany have the highest churn rates, with around 800 and 900 customers respectively, while Spain shows fewer than 400 churned customers. This emphasizes the need for targeted efforts in these regions to address churn and retain customers.

Question 7: Is there a significant difference in churn rates between genders?

This insight indicates a higher churn rate among female customers compared to male customers. It's crucial for the bank to devise strategies to retain both female and male customers.

It's surprising to note that despite having fewer female customers compared to male, they are exiting the bank at a higher rate.

Question 8:What is the average age of customers who churned compared to those who stayed?

We notice that the average age of customers who churned from the bank is 38, while the average age of those who did not churn is 43. This suggests that younger customers are more likely to leave the bank compared to older ones. Additionally, it might be worth exploring why customers in their late thirties are more prone to churn and if there are specific factors contributing to this trend.

Question 9: Does tenure with the bank impact the likelihood of churn?

It appears that the tenure with the bank doesn't significantly impact the likelihood of churn. This suggests that customers with both short and long tenures are equally likely to churn. However, we might want to explore other factors such as customer satisfaction or product offerings to understand why tenure alone doesn't seem to affect churn.

Question 10: What is the distribution of account balances among customers who churned?

It's surprising to see that even customers with a significant bank balance are leaving the bank. We observe that some customers with zero balance and even those with balances ranging from 50,000 to 200,000 are among those who exited the bank.

This suggests that factors other than account balance, such as customer satisfaction, banking services, or personal circumstances, might be influencing their decision to leave. It's essential for the bank to delve deeper into these reasons to understand why customers with substantial balances are churning.

Question 11: How does the number of products held by a customer relate to churn?

The insight reveals that customers who are engaged with a higher number of bank products, ranging from 1 to 4, are exiting the bank. 

Surprisingly, those with just 1 or 2 products are more likely to be non-churned customers. This suggests that the bank's strategy for product engagement might need reassessment. 

It's essential to explore why customers with multiple products are churning, as it could be due to dissatisfaction with certain services or other underlying factors. 

Question 11: Is there a difference in churn rates between customers with and without credit cards?

It's surprising that people who have credit cards are leaving the bank more often, even though those without credit cards are also leaving, but not as much. This suggests there might be issues with the bank's credit card services or with how satisfied customers are with their credit cards. The bank should look into why this is happening and try to keep more customers, especially those with credit cards.

Question 12 : Does customer activity (e.g., logins, transactions) affect churn rates?

It's evident that inactive customers, especially those who don't use online banking or perform transactions frequently, are more likely to leave the bank compared to active customers. This highlights the importance of engaging customers and providing them with reasons to stay, such as offering personalized services or incentives to use online banking features.

Question 13 : What is the satisfaction score distribution among customers who churned?

It's surprising to note that customers who churned had previously provided good ratings indicating satisfaction with the bank's services. 

Question 14 : Relationship among churned and complain

The data strongly indicates that customer churn is closely linked to prior complaints. This underscores the critical need for proactive and efficient handling of customer issues to minimize churn and bolster overall customer retention.

the below one shows about the correlation for the exited as churn or non churned customers.
This correlation provides insights into the relationship between various features and customer churn. Features that are positively correlated with churn indicate that as those features increase, the likelihood of churn also increases. Conversely, features that are negatively correlated with churn suggest that as those features increase, the likelihood of churn decreases.

conclusion:

In summary, our analysis of bank customer churn highlights significant trends and challenges. Despite efforts to retain customers, younger demographics and those with credit cards show a propensity to leave. 

Surprisingly, factors like account balance and satisfaction don't exhibit a clear relationship with churn, while customer engagement emerges as a critical determinant. Addressing customer complaints promptly and implementing targeted strategies to enhance engagement are essential for mitigating churn and improving retention rates.