Predictive Analytics Framework for Banking

This case study outlines the collaboration between Tiger Analytics and a leading European bank to enhance customer engagement and cross-selling through a predictive analytics-driven modeling framework. The primary objective was to identify the next best products for customers by utilizing a data-driven approach during inbound customer interactions. The study details the challenges faced by the bank, including a lack of comprehensive customer behavior insights and difficulties in managing large datasets. Tiger Analytics addressed these issues by conducting thorough data exploration and refining the data to create a 360° customer view analytical dataset. This dataset integrated various customer and product data, enabling the development of sophisticated algorithms to predict cross-sell propensity. The framework ultimately helped the bank identify optimal product recommendations for each customer, leading to increased product uptake and revenue, as well as improved marketing efficiency and customer satisfaction.