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Banking on big data

(Image credit: Image Credit: Everything Possible / Shutterstock)

Despite the dislike of the term by some, the importance of Big Data continues to grow and with it, its potential for benefitting the retail banking industry. As with other industries, many banking services and insurance organisations are working to adopt a fully data-driven approach to grow their businesses and enhance the services they provide to customers. Some are already ahead of the curve, others are lagging behind, at varying levels of Big Data maturity.

Whilst data collection has long been vital to the retail banking sector, the amount of data being collected continues to grow exponentially. However, more does not necessarily mean better and some banks are still working with legacy systems, leaving them struggling to keep pace with changing customer dynamics and the digital landscape. Big Data is most often defined by the ‘3 Vs’ of Volume, the actual amount of data growing, Velocity, the fact more and more data is in real-time and Variety, reflecting the changing structure and kinds of data. Handling Big Data is not just about having more, it’s about being able to get the right data from within the gathering storm of data and then, putting it to use.

Today’s consumer enjoys the freedom of using mobile internet and smart devices and interacts on social media, as well as a range of other digital apps, anywhere, anytime. Thanks to the application of data analytics, customers have come to expect content and offers tailored to their own interests and shopping and browsing habits, usually delivered to them in real-time.

Accustomed to receiving relevant insights and offers at the right moment in other areas of their lives, customers now expect the same experience from their banks. Due to the nature of the business, banking services are unlikely to elicit the same warm, engaged feelings from customers as, for example, their favourite retail brands. However, there must still be a real and relevant connection between bank and customer. This is where Big Data analytics need to be employed. Not capitalising on the growing amount of data over time has left some banks little connection with, and limited understanding of, their customers. In turn, this naturally limits their ability to tailor products and services and create content that resonates with those customers.

In today's competitive environment, customers are not only more informed and accustomed to receiving such content, but switching banks is also easier than ever before, sometimes with clear monetary incentives. The combination of these factors makes it imperative for banks to form relationships with those customers as individuals in order to retain them.

Value of analytics

In fact, the number of current account holders switching bank or building society reached a two-year high last year according to payments body Bacs. During the first three months of 2018, more than 273,000 switches were recorded, a 10 per cent increase on the same period in 2017. As competition grows increasingly fierce, banks must be able to understand customer preferences and motivation and create a seamless experience that anticipates their expectations in advance.

With growing switching, the opportunity is significant for challenger banks as well as the large, established banks. A perennial truth of business is ‘know your customer’. Large or small, the ability to know your customer, and prospects, is fundamental to serving relevant marketing and great customer experiences. You just can’t have those outcomes without it. For the growing challenger market, there’s a great opportunity to not be restricted by large legacy systems and to design a unified data layer, across the right data and technology to put the customer first. In some ways, just starting out puts the challengers at an advantage despite the disadvantage of scale.

An additional benefit of this data-driven customer interaction is that attrition and loyalty can also be measured. This is important because analytics measuring attrition can also help identify when and why customers are switching. This can then enable retail banks to target specific content to those who are considering a move.

Alongside driving retention, Big Data can also be applied to answering unmet customer needs, cross-selling potentially useful products to existing customers by analysing their spending potential and identifying what they might need. This more precise and softer selling is particularly relevant in the post PPI landscape which generated huge distrust in the hard sell.

Data collection and security have, for good reason, historically been priorities for banks. However, most analytics, strategies and efforts have focused on regulatory requirements, rather than value creation. There are many areas where analytics can provide rich insights and bring value to processes and operations. These range from facilitating improved fraud management, credit management and risk management to mitigating operational risks and losses. Historically fraud detection was previously based on customer spending patterns, now analytics is integrating complete customer profiles to detect fraud. Additionally, predictive analytics can be used to look at triggers that may affect credit exposures.

From delivering a better customer experience, through more relevant marketing, to channel spend optimisation and fraud prevention, such is the value of analytics that, according to a 2016 report by SAS and the Centre for Economics and Business Research, the value of Big Data could be worth £322bn to the UK economy by 2020 and retail banking is forecast to be one of the sectors that will experience most economic benefit – estimated at more than £16bn.

Looking to the future, the desire for analytics to support and drive the retail banking sector forward is only ever going to increase. The important ‘watch out’ is that the increasing volume, velocity and variety of data, will be of limited benefit sitting in silos. All banks, indeed, all businesses require strategies to create a Unified Data Layer, to realise the potential of their data, to know their customers and to earn success as their reward.

Lisa Andreou, Sales Director, UK, Acxiom
Image Credit: Everything Possible / Shutterstock