The problem

For insurance companies, the main driver of growth is product sales, however the preferred way is through existing clientele, as finding new customers is a much more expensive process. Therefore, companies rely on the historical data in their possession to understand customer behavior, make more targeted product promotions, and thereby extract the maximum possible capital that a customer can allocate. A critical factor in identifying a customer's profile is their net value to the company (Customer Lifetime Value - CLV), which takes into account the difference between the total amount of revenue received by the company from the customer and the costs incurred by him during their relationship.

The purpose

Predict customer lifetime value.

The solution

By using machine learning and artificial intelligence models based on historical customer data, a safe prediction of a customer's future net worth to the insurance company can be made.

The benefit

Forecasting the amount of money a customer will potentially cost the insurance company as well as the profit it can bring to the insurance company is considered necessary to give a clear picture of the amount of money worth spending to acquire, retain and service of.