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Banking Sector Customer Attrition Records
Finance & Banking Analytics
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About
Understanding why clients cease their relationship with a service provider is a cornerstone of sustainable business growth. These records offer a detailed view of consumer behaviours, financial health, and demographic profiles, allowing organisations to identify churn risks before they occur. By focusing on retention, companies can significantly reduce the high costs associated with acquiring new clients and foster long-term loyalty. The insights provided here assist in building a thorough view of customer characteristics that lead to attrition, enabling preemptive action and more informed decision-making.
Columns
- RowNumber: A sequential index used for record organisation.
- CustomerId: A unique identifier used to track individual clients without revealing personal identity.
- Surname: The customer's family name, which can be utilised for personalised marketing strategies.
- CreditScore: A financial indicator reflecting the customer's creditworthiness and financial health.
- Geography: The specific location of the customer, useful for uncovering regional patterns in market behaviour.
- Gender: Demographic information used to analyse trends across different genders.
- Age: The age of the client, which significantly influences purchasing habits and loyalty tendencies.
- Tenure: The duration of the customer's relationship with the company.
- Balance: The amount of funds in the customer's account, indicating their level of financial investment.
- NumOfProducts: The total number of services or products the customer currently uses.
- HasCrCard: A binary indicator showing whether the customer possesses a credit card with the firm.
- IsActiveMember: A status marker indicating if the client is actively engaging with their account.
- EstimatedSalary: The approximate annual income of the customer, used to gauge financial well-being.
- Exited: The target variable indicating whether a customer has churned (1) or remained (0).
Distribution
The information is delivered in a CSV file titled
Customer Churn new.csv with a file size of approximately 624.82 kB. The archive consists of 10,000 valid records and 11 primary columns, maintaining 100% data integrity with no missing or mismatched entries. The dataset is structured for immediate use in analytical software and is scheduled for annual updates.Usage
This resource is ideal for developing and testing binary classification models, such as Logistic Regression, Random Forest, and Neural Networks. It is well-suited for identifying high-risk customer segments and designing targeted retention incentives. Analysts can also use these records to conduct market basket analysis by looking at the number of products held or to perform demographic studies to improve the overall customer experience and revenue growth.
Coverage
The scope of the data includes a broad demographic range, with ages spanning from 18 to 92 years. Geographically, the records include multiple regions, with France being a prominently represented market. The data provides a detailed look at various financial statuses, including a wide range of credit scores and estimated salaries, ensuring a diverse representation of consumer financial backgrounds.
License
CC0: Public Domain
Who Can Use It
Data Scientists can leverage these records to refine their skills in predictive modelling and feature importance analysis. Banking and Financial Analysts may utilise the data to understand the drivers of account closures. Additionally, Retail and Subscription-based Businesses can find this a valuable primary source for developing strategies to maintain a loyal customer base and gain a competitive advantage.
Dataset Name Suggestions
- Global Consumer Churn and Loyalty Archive
- Banking Sector Customer Attrition Records
- Financial Behaviour and Churn Prediction Index
- Predictive Analytics for Client Retention
- Demographic-Driven Customer Churn Dataset
Attributes
Original Data Source: Banking Sector Customer Attrition Records
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