5 Reasons Why Banks Must Use Predictive Analysis

Beth Schultz, in her blog post on Predictive Analytics revealed an interesting story about how her friend was offered refinancing of her mortgage by her bank, Chase Bank. This was the bank’s reward to her for being a long standing loyal customer. 

How could Chase Bank probably have arrived at such a decision? The answer lies in Predictive Analysis. 

 

Today, as banks and financial institutions realize how imperative advanced real-time analytical solutions are for running their organizations, they are also looking for constructive predictive analysis tools. 

Here are some of the uses of predictive analysis for banks:

Right Product for the Right Customer:

Using predictive analysis tools, banks and financial institutions can track individual customers for specific buying habits and derive a distinctive pattern, using which they can easily categorize the customers on different parameters and offer them services and products specific to their needs and wants.

For example: consider that one of your customers is an NRI, whose account, over a period of time has seen a lot of transactions for buying or selling of property, indicating that he is investing heavily in real estate. Perhaps then, wouldn’t a tailor made home loan with special benefits to NRIs be just the right product for him? This is also an effective way to decrease customer attrition.

Manage and Maintain Brand Reputation:

Are your twitter streams bombarded with tweets from dissatisfied customers or is your Facebook wall filled with negative comments and complaints about your products and services? Well, left untreated, this negative sentiment could take on giant propositions and do grave damage to your brand reputation.

Using predictive analysis, banks can assess the reason for increased negative sentiments about their brands, fix the issue and thus prevent these instances from snowballing into a PR crisis.

Detect Fraud:

Are some of your customers always finding their way to the defaulters list? Repeatedly? May be they are not legitimate customers at all. With Predictive analysis, you can easily find out.

Better Customer Insights:

Banks and financial institutions nurture a huge repository of customer information both personal and financial. But the key lies in using this information effectively to increase revenue.

For example: using predictive analysis, if an IT manager took a home loan and a car loan together but has now been defaulting every now and then on both EMIs, then may be it is an early indicator that he could have difficulty repaying both the loans. 

Thus, predictive analysis tools are extremely beneficial to banks with regard to improving customer relations, increasing revenue and strategizing their marketing initiatives.

Shout Analytics provides cutting-edge predictive analysis services to BFSIs. So, if you are convinced that your organization needs predictive analysis tools, contact us at info@shoutnalytics.com