The volume, variety and velocity of data created in the digital age is making data usage a strategic priority for banks of all sizes. Data is often described as the ‘new currency’, and rightly so, as the ability to create value from this ever-growing resource
will determine future success.
Of course, data has always been valuable, but there are three factors that have changed the way it is harnessed and analysed. The first is the sheer amount of data available. Some 90% of all data today was produced in the last two years. Secondly, increased
processing power means data can be gathered at a faster rate than ever before. Lastly, and perhaps most importantly, a new profession has come to the fore, precipitated by the first two – that of the data scientist.
Using the skills of these data-savvy professionals, patterns can be found in data sets which would have otherwise been left untapped. Data scientists look beyond stark numbers to include insights relating to anthropology or social history, creating a more
holistic view of customer behavior and their propensity to make financial, spending and other decisions in the future.
There are different maturity levels when using data to understand customer motivations. Many organizations can determine what their customers are doing and why they’re doing it – these are the first two levels. The third level of data maturity is using the
understanding gained from the first two to predict future behavior. Few, however, achieve the fourth level of maturity, which is using data to encourage customers to make a decision, like buying a product.
Take, for example, a bank which notices the appearance of a direct debit for a gym membership in their customer’s account alongside a subscription to a healthy-eating magazine. If this activity is unusual for the customer, it may show that they have made
a commitment to improving their health. Here, we have the what and the why. Going forward, it would be reasonable to assume that other changes in lifestyle might occur in the same vein (the third level). But what then might a bank be able to do to support
the customer on this new path? This is where the ability to use owned data in combination with other data sets becomes invaluable.
Through examination of readily available weather and traffic data, as well as knowledge of the customer’s local area, the bank could determine that cycling to work might appeal – and suggest the customer purchases a bike from a partner retailer as part of
a green-living initiative. The bank could offer a special facility loan for a bike, as well as other equipment, allowing the customer to take advantage of its business relationship with the retailer through special discounts.
In this instance, the discussion with the customer at the branch changes and the bank becomes a source of information and advice that is hugely valued by the customer. This is especially true when it provides a great offer, such as an interest free credit
card to pay for everything and consolidate multiple balances.
Of course, banks must tread lightly when using data to advise and suggest new services for customers. ‘Big Brother Syndrome’ is something that can turn customers off, but as long as their data is used transparently, the likelihood of them appreciating the
insights gained and services offered will surely grow over time.
It must be remembered that banks aren’t unknown entities in their customers’ lives – in fact, they are unique in the levels of trust customers have in their ability to look after their money. So, by adopting a business strategy which builds upon this trust,
and by using the vast amounts of data they have in a transparent way, banks are well placed to transform how they deliver services.
Banks also need the tools and platforms to enable data scientists to navigate their way through the huge volumes and varieties of information being gathered at ever higher velocity. Here I would suggest adopting a Platform-as-a-Service approach, which will
allow banks to bring data-savvy software developers into an innovation ecosystem.
To truly harness the limitless possibilities that data analysis and data science provide, banks must start thinking differently about their role in customers’ lives. They must also recognise that the services they provide are becoming increasingly commoditized,
as evidenced by the rise of neo-banks, loans and payments providers, and also agile Fintechs, and adapt accordingly. Becoming a trusted advisor through the use of data deepens the relationship with the customer and will ultimately transform the way customers
see and use their banks – a must if they are to adapt and maintain competitiveness in the digital age.
External | what does this mean?