Problem to solve
In most businesses some of the customers leave
Knowing in advance that specific customer will churn gives you an ability to reach him out and retain
Competitive advantage
- Current evolution of financial services implies rapid digitalisation of the whole value chain of banking industry. As a result, we are witnessing a shift from traditional bank clients, which are still visiting local branches, towards a new generation of customers, which do not need them and rely purely on online products.
- Before, while predicting the moment of losing a client, banks could consider only a limited number of factors, such as - client lost his job, changed it, moved to another country, or even died. Due to this limitation, the quality of analysis was poor, that’s why banks were used to invest less in such research.
- The life of modern clients became way more dynamic, making it easy to lose them. The breadth and depth of factors describing their behaviour as well as the amounts of available data grew significantly, which requires brand new models for predicting potential churn.
- To tackle this problem, we are started developing Churn ML - a tool powered by enhanced machine learning algorithms, that predicts and prevents Churn for mobile and online banking.