You don’t need to be big to use big data in banking

The growth of mobile banking and payments has opened up the market to a new breed of ‘challenger’ banks and fintech companies. Mobile payments nearly reached the £1bn mark last year – which, as a proportion of all payments, is still only a couple of percent, but its growth is likely to be non-linear. In their most recent industry report, KPMG noted that more than 50 institutions have been granted a banking licence in the UK alone since 2008. Look at China if you want a vision of the likely future of mobile payments in the UK: its mobile payment market has grown to $16tn, thanks largely to the success of WeChat and AliPay.

In the increasingly crowded market of the ‘big four’ (HSBC, RBS/ Natwest, Lloyds, Barclays), established challengers (e.g. First Direct, TSB), supermarket banks, and an emerging group of specialist fintech companies (e.g. Monzo, Revolut), there is pressure on the incumbents to re-establish their value against the technology-driven alternative of the competition. Their success will depend, more so than any other technology, on their capacity to use big data.

The applications and value of big data within banking are unlimited.

Leveraging customer intelligence

Digital banking, as well as card and mobile payments, have provided banking with a surge in customer data. Last year was the first in the UK where card payments exceeded cash. For banks, this means more information on customer spending patterns. First party data from a bank’s website, app and social media pages, as well as second and third party data from data brokers such as Experian and Equifax, allow banks to construct increasingly detailed customer profiles.

Greater customer understanding is valuable in so many ways, from improving services to updating branding and positioning. Banks are now able to understand more than just their customers’ financial characteristics; the emergence of big data in banking provides insight into people’s personal lives too.

This data can be used to personalise their advertising, tailoring the content according to the right audience and the right moment. Done properly, data can be the most valuable asset in any marketing campaign.

Using data for marketing: challenger banks vs established banks

The more established banks have a natural advantage in terms of data supply: they have more customers, and therefore more first party data. Theoretically, too, the larger challengers and big four should have greater investing power, allowing them to capitalise most successfully on the benefits of big data. In a survey taken in 2016, PwC asked a sample of banking executives which types of banks would benefit most, and which would be most threatened by big data by 2020.

What this survey shows is that established banks somewhat underestimate the power of big data to grow smaller businesses. They also overestimate the advantages of size.

First party data isn’t a panacea. Take Facebook ads, for example. Facebook interprets signals from a user’s browsing behaviour to predict when they are more likely to purchase a product or service (‘in-market’ audiences). Facebook also provides data on ‘life events’, e.g. when someone has just moved house and may therefore be more interested in switching banks, for example.

With Facebook having done the analytical heavy lifting, advertisers of any size and with any amount of first party data have the opportunity to target highly valuable audiences. Admittedly, being able to layer your own customer data on top of this is an asset (filtering out existing customers from promotions aimed at new customers, for example), but certainly not essential.

Challenger banks have also proved more adept at converting customers into ‘fans’, i.e. people who are loyal to the brand and feel a sense of shared identity or have common goals. With their community forums, referral system and Trello board that lets users vote for future features, Monzo is a case in point. Aside from enhancing the lifetime value of their customers, this also generates extremely useful data via social media interactions. In other words, though traditional banks may have more customer data, challenger banks may have more useful customer data.

Tech drives growth

We are living in a unique era in the history of business, in which the combination of data, the internet, AI and globalisation can generate industry giants in the blink of an eye. What else explains Amazon and Google’s current success? Primarily, it was through their use of big data. If Revolut can achieve unicorn status in only three years, what can it achieve in ten? The same applies to a number of other promising fintech companies.

These are only a few examples of the applications of big data. If you are a financial services brand, think of how valuable it could be to your customer service, product cross-selling and risk management. Big banks would do well to keep a close eye on what the smaller banks are up to, because this is where the bulk of the innovation will originate. You don’t need to be big to be good at big data.

This article originally appeared in The Drum Network Finance Supplement. For more information on how to get involved, please contact tehmeena.latif@thedrum.com

Dan Gilbert, chief executive officer, Brainlabs