A leading commercial bank in Sri Lanka with an established credit card customer base of over 100,000 subscribers were looking to further expand their growing customer base and enhance their services, they wanted to get detailed insights of their customers behavior. They planned to launch a marketing campaign to acquire more profitable credit card users. They were also curious to identify which users might default on a credit card payment.
Using predictive analytics they did just that. They used analytics to figure out which of their customers who didn't already have credit cards were more likely to opt for one, greatly improving the effectiveness of their marketing efforts. For example, today, when their marketing team calls up potential credit card customers, they only contacts those recommended through a model, resulting in 80% sales on all calls made! Furthermore, by identifying which customers are more likely to default in advance, they are able to reduce the overall default risk faced by the bank.
The success rate of the Bank's marketing efforts have grown more than 50% today, resulting in prospects which are not even the bank's traditional customers, a feat previously thought unimaginable. N*able built two predictive analytical models to help them achieve their goal. Brainstorming with credit card experts and marketing field officers from the Bank to understand the parameters that govern credit card customer behavior, they enabled this predictive tool.
Photo Credits: Richard Tilney-Basset
Target Accuracy, Reduce Risk
Introducing analytics to enhance customer acquisition
by: Niruban Satchithanandakumar