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Global Banking Customer Segment Data
Finance & Banking Analytics
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About
This synthetic dataset models the customer base of a global retail bank, offering essential demographic details and key aggregated financial performance indicators (KPIs). The data was created to allow users to quickly ascertain customer figures based on specific dimensions across key markets without relying on sensitive real data. It is structured as aggregated metrics, meaning each individual row summarises the characteristics and financial activity of multiple customers. This makes it an ideal resource for developing analytical tools, such as dashboard applications, that require high-level, segmented banking metrics.
Columns
The dataset contains 23 columns, which are divided into customer dimensions and aggregated measures:
- Market: The country where the customer's account is domiciled (9 unique values).
- Proposition: The assigned product or service tier the customer belongs to (3 unique values, e.g., Bronze).
- Primary: A binary indicator (Y/N) specifying whether the institution is the customer's primary bank.
- Tenure: Categorical representation of the years the customer has maintained an account (4 unique ranges, e.g., 1–3 years).
- Age: Categorical representation of the customer’s age (6 unique ranges, e.g., 25–35).
- International: A binary indicator showing if the customer holds an account in another country (e.g., Domestic).
- CA, Card, Insurance, Investment, Mortgage: Boolean flags indicating whether the customer holds a current account, a bank card, insurance, investments, or a mortgage, respectively.
- NPS: The customer's Net Promoter Score (3 unique values, e.g., Promoter).
- Digital: A binary indicator of whether the customer is classed as digitally active.
- Numcust: The total count of customers that correspond to the dimensions specified in that row (the core aggregation measure).
- TRB: The Total Relationship Balances held by all customers in that aggregated row (average £1.71 million).
- Revenue: The total revenue generated from the aggregated customers (average £29.8 thousand).
- Primary_cust, Digital_cust: The counts of customers within the row considered primary or digitally active.
- CA_holders, Card_holders, Ins_holders, Inv_holders, Mort_holders: The counts of customers holding specific products (Current Accounts, Cards, Insurance, Investments, Mortgages).
Distribution
The data file, typically available in a format such as CSV, is 70.19 MB and includes approximately 498,000 records. The dataset structure is aggregated, with dimensional attributes typically located in the initial columns and quantitative measures (KPIs) positioned towards the right. This resource is static and has an expected update frequency of Never.
Usage
This data is ideally suited for strategic planning, model training, and analytical reporting within the financial sector. Specific uses include:
- Developing and testing new customer segmentation models.
- Benchmarking key performance indicators (KPIs) across different international markets.
- Building internal or external interactive dashboard applications (like Dash applications) to visualise customer metrics.
- Conducting simulations and financial modelling based on synthetic but realistic bank customer data.
Coverage
The dataset reflects the customer base of a global retail bank, encompassing 9 distinct geographical market areas. Customer demographic scope is defined by age brackets, tenure ranges, and product proposition tiers.
License
CC0: Public Domain
Who Can Use It
Intended users include:
- Financial Modellers and Analysts: For simulating banking scenarios and testing risk or revenue models.
- Data Scientists: For developing predictive algorithms related to product uptake, retention, or customer value.
- Application Developers: For creating dynamic dashboards and visualisations of aggregated banking statistics.
- Academic Researchers: For studying retail bank customer behaviour and demographics using non-proprietary data.
Dataset Name Suggestions
- Synthetic Global Retail Bank Customer KPIs
- Aggregated Financial Customer Demographics
- Global Banking Customer Segment Data
Attributes
Original Data Source: Global Banking Customer Segment Data
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