Major Swiss bank

Problem

• Significant churn in existing customer base which limits overall growth ambitions in saturated Swiss market
• Large number of customer data available, which was not systematically analysed
• Client advisors often surprised if customers leave

Solution

• Early warning system was created based on a machine learning model to identify customers at risk of leaving or withdrawing a large part of their assets (attrition risk)
• System based on regular monitoring of client behaviour (e.g. transaction behaviour, the intensity of engagement) to predict the attrition risk
• A customer group specific retention approach was developed to pro-actively contact customers with high attrition risk

Impact

• It could be proven that the machine learning model identifies the right customers at risk
• Retention approach has proven to be highly effective since the churn rate of customers at risk could be significantly reduced
• Client experienced strong business benefits, since revenue outflows due to customer churn could be reduced