Discovering hidden associations in banking data

How can associations and relationships between variables be identified? In this example, we analyze anonymized banking customer data, and identify hidden associations to increase profitability. We also explain how the same technique can be applied to other types of data.

Analyzed data:

The following anonymized variables were made available by a bank:

• Age
• Income
• Number of cars
• Number of children
• Sex
• Region (ex: city)
• Married
• Credit limit
• Opened a savings account
• Checking account balance
• Customer since (in months)
• Number of support calls
• Mortgage loan
• Defaulted on payment