Predictive Analytics and Banking Customers

Thursday 09th, June 2016

predictions photo Photo by kathyturner1

Satisfying customers is something that all businesses including banks aspire to do. And that is not easy. The customer of today is evolved. He is demanding. He wants to be treated as an individual and wants to be made to feel that some product offering was personally addressed to him.

On the other hand banks have questions that they would like answers to –

  • How can they ensure loyalty from their customers?
  • How do they ensure loyalty from its high-value customers especially?
  • How do they attract different kinds of customers?
  • How do they retain all these customers that they have attracted?
  • How do they reward their loyal customers?
  • What additional product can they sell to their existing customers?
  • How can you understand a customer?
  • What motivates a customer and why?
  • How can they make the right offers to the right customers at the right time?

This is where Predictive Analytics comes in.

There is a tremendous amount of real-time customer data that is available today for any business to tap. Banks are no exception to this. In fact Banks have access to all kinds of information about each of its customers.

Predictive Analytics extracts information from existing data sets – it finds patterns in the data and based on this, can predict probable and possible future outcomes and trends. It cannot predict what will happen in the future. What it does is to forecast what might happen in the future – with some acceptable level of reliability. It also includes some what-if scenarios and does risk assessment.

Predictive Analytics uses many techniques, including data mining, statistical modeling and machine learning to help analysts make future business forecasts. You can take the data that you have currently along with data about the past and derive insights from this, which will help you better understand customers, products and partners. You can also identify potential risks and opportunities for a bank. Banks can identify and respond to new opportunities quickly.  Customers can be managed better.

Banks can tell what product will interest a certain customer. Not a one size fits all kind of approach – but since he knows the customer using predictive analytics, he knows what will interest the customer and is now able to send him a highly personalized message that is relevant to him. Based on the kind of products that the customer has been interested in, Banks can develop products that this customer would be interested in, in the future.

In the same way, a Bank can offer other products that he would be interested in. All this is based on an analysis of his current behavior. And the more products a customer invests in, the stronger his relationship with the Bank. And this leads to long term profitability both from him, and from the others that he would recommend the bank to!

At the end of the day, all financial products are more or less the same. Banks need to do all they can to retain the customers they already have and build on them. Sell them more products. Make the relationship with them strong. Make sure they pick up any signal that a particular customer is likely to churn and leave this Bank for a different one. Find out why they would want to switch. And address that. Predictive Analytics can help track that by studying his spending patterns and his product usage patterns. You know he likes this product – and based on this, you can recommend something else that he would like, to him.

Speaking of tracking – if some customers have loans with a bank, his spending patterns can be tracked and monitored. This will bring down cases of delinquency – as any spikes in spending can be tracked. Any late payments or frequent ATM withdrawals can be tracked.

In general, the way a bank engages with its customers will radically change with the presence of Predictive Analytics. It would be an intelligent and informed engagement – where the Bank knows its customer. Knows what he is interested in. Knows what he is likely to be interested in. Knows what will work with him and what won’t. And the result is a growth in revenues, satisfied customers who will recommend your brand to others and a drop in delinquent cases.


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