Churn Prediction Solution
For BFSI Industry

INDUSTRY

FinTech

CORE TECHNOLOGY

Python

Large banks, finance services and insurance firms manage lakhs of customers, who bring in thousands of crores worth of assets with them.

It is essential for these businesses to engage customers by providing them with new products by upselling to existing customers or increase customer retention or acquire new customers to continue to generate more revenue. This makes machine learning the best weapon in the retention arsenal and churn prediction the most widely used big data use case.

Corporations spend a lot of money in developing strategies to fight customer from disengaging. Using churn prediction, it will now be possible to detect those customers who are likely to disassociate in the coming month and hence employ all efforts towards those identified, rather than just shooting in the dark.

Challenges

  • Inability to gauge which customers are likely to discontinue
  • Inability to employ individualized customer retention strategies, thereby not fully getting the return on investment on such strategies
  • Not being fully able to leverage ROI on strategies to increase revenue in and around customer engagement

Solution

Developed AI Solution to determine the customer propensity for churn.


Deep learning to manage nuances and vastness of customer data


Targeted customer retention scope for better ROI

Tools & Technologies

  • - scikit-learn
  • - Classification
  • - Keras
  • - AERTIFICIAL Neural Network
  • - Python
  • - scikit-learn
  • - Classification
  • - Keras
  • - Artificial Neural Network
  • - Python
Business Benefits
  • Automatic churn prediction for all customers by machine periodically
  • No delays due to manual prediction based on analytical reports
  • Impactful difference in retention before and after churn
  • Taking proactive action beforehand to improve success rates