Customer Segmentation and Targeting

USECASE/DOMAIN: Conversion Rates of the bank for short term loans were low, leading to reduced sales. It was difficult for the company to target eligible customers with buying intent.We can segment the customers and recommend products and services for existing customers by using customer demographic details, bill payment/ balance history, support tickets, and call and data usage (where available) of customers.

FIBS MODEL: We used Deep Convolutional Neural Network on 18 months of data for existing customers including demographics, history & activity on bank accounts and credit scoring to predict customers most likely to purchase.

Unlike traditional models, AI learns continuously. This ensures the model becomes more accurate as new data is fed and does not become obsolete.


Customer experience

Organisations that enhance their existing customer value focus their analytical efforts on better targeting of customers and optimising existing products and services that are offered to the customer. To do this analytics are focused on getting a broader view of the customers, used to improve:

  • direct marketing
  • predicting retention (and cancellations) of customers
  • personalised offers
  • the propensity to buy
  • targeting idle customers
  • selecting the right marketing channels
  • setting the right price
  • selecting the right promotions


Sales and customer intelligence

AI is deployed to gather and analyze customer data and intelligence to give business development teams new insights, sales leads and recommendations for the ‘best next action’ to develop the relationship and drive forward a sale.


Customer services

This is one of the most common applications of AI in financial services. Instead of client service executives having to work through hundreds of emails manually and many of BSS (business support system), AI can predict and prepare an appropriate proactive execution steps targeting the right products to the right clients.