Predictive analytics and its role in modern digital banking

data analytics, analysis, information, digital

Some of the most significant recent trends in financial services – such as the ongoing growth of the mobile channel and the expansion of the fintech market – have demonstrated that the evolution of the industry is being driven by technology.

One technology that we can expect to play an increasingly important role in the years to come is predictive analytics. This technology can help banks deliver a valuable, next-generation experience for their customers.

What is predictive analytics?

Financial institutions (FIs) can use predictive analytics to harness their knowledge of what has happened in the past to come up with an assessment of what will happen in the future. This can make a big difference to the customer experience, strengthening brand loyalty by showing consumers that their provider is engaged with their needs and invested in delivering a beneficial, relevant service.

In the retail banking sector, predictive analytics is an approach that FIs can use to help their customers prepare for future events and financial commitments, based on historical and transactional data.

It can incorporate various other technologies and processes, such as data mining, predictive modeling, machine learning and artificial intelligence.

By analyzing past transactions and financial activities, the system can help users to plan more effectively for the future.

One example of how predictive analytics can function in the digital banking space is by delivering alerts to customers when they are likely to become overdrawn, based on historical spend analysis. This allows customers to take action before the upcoming bill payment or financial event makes them overdrawn.

In a recent interview with Fintech Innovation, Zhi-Ying Ng, Forrester research analyst for e-business and channel strategy, pointed out that developing next-generation digital banking capabilities is a key focus for many banks at the moment. She said deploying predictive analytics is at the heart of this, as providers look to help customers achieve their financial goals.

“Some banks are really trying to see how they can really help customers – above and beyond just moving money, or doing very basic transactional capabilities, and trying to automate some of the tasks for them, so it’s a proactive service,” the analyst said.

The need to personalize

One of the most important benefits of predictive analytics is that it helps FIs to deliver a bespoke, personalized service to consumers – something that is becoming increasingly important in the modern world.

With a new breed of fintech providers and smaller, more agile banks offering a genuine alternative to established FIs, it’s no longer enough to take a mass-market, ‘one-size-fits-all’ approach.

Users of financial services are increasingly demanding products and solutions that are relevant to them and reflect their personal goals and circumstances. Predictive analytics can help banks to achieve this by studying data on individual consumers and using the findings to offer practical recommendations and support.

This can be delivered as part of a next-generation digital banking experience, through a customized app or digital platform where the user can get a detailed view of their financial situation.

Brands that are able to deliver this level of personalization and value to their customers will see the benefits, through increased brand loyalty and, as a result, more opportunities to generate revenue.


Image: chombosan via iStock

Written by Bryn Coulthard

Bryn Coulthard

Based in the UK, Bryn is part of the Digital Banking team at NCR with responsibility for global offerings and opportunities. Previous to NCR, Bryn spent 15 years in IT for a UK retail bank working in a variety of Software Development and Architecture roles.

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