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Hyper Personalised Customer Interactions in Banking

Raj Dalal / 2 min read.
October 4, 2016
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In todays tight world economy, under-stress financial institutions, including banks, are looking for fresh solutions to help grab new customers, retain the profitable clients, and eventually boost the bottom line.

Banking on Big Data analytics is the way forward. The lines between the real world and digital finance are fast blurring. Increasingly, FIIs and banking executives globally are asking – how can analytics help in optimizing bank-client relationship? The answer lies in the combination of customer information base, technology and analytical methods.

Take what US-based Novantas did recently for one of its clients, a well-known US bank, for example. This global leader in analytic advisory services and technology solutions for financial institutions, implemented a solution for the 10 million customers strong bank that enabled the latter to conduct a far more profitable business than ever before by using persona-based pricing per customer.

Solution highlights:

Traditionally, banks have always offered honeymoon rates to attract new deposit monies with the hope that customers will keep their monies with the bank for many years to come. Banks hope that by doing so, the short term loss will be recouped with customer inertia to move their funds over to another bank once the honeymoon period is over. Almost no science is applied to personalising the price premium at an individual customer level.


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For its client-bank, Novantas decided to change that. It developed an analytical model that mapped personas by looking at, among other things, rate sensitivity – that is, how much of a premium needs to be offered to initiate action.

Outstanding results:

  • Marketing execution cost of the bank came down by 50%
  • Reduced promotional expenses were reduced by as much as 60%

Novantas built its solution on Cloudera Hadoop, one of the most advanced data management and analytics platforms being used by some premier FIs to optimize RoIs. Combined with Hadoop and Sparks ability to process massive amounts of information at a low cost, Novantas has enabled its clients like the bank to granularly target customers based on their responsiveness to price and the likely retained value from that offer.

BigInsights was recently contracted to study the reasons behind Novantas’ huge success story. To get the insider stuff on how Novantas used data analytics solutions to help its clients, click here to read the case study (Note: Registration Required).

Categories: Strategy
Tags: analytics, banks, Big Data, big data analytics, Financial Services

About Raj Dalal

Raj Dalal is an expert and go-to person for the application of Big Data Analytics in industry. He is also an IoT Advisor focused on industry applications of technology.

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