Unlocking the potential of Big Data
It’s a familiar story: austerity, an economy in and out of recession and no end to the tunnel in sight. At the centre of the national crisis sits a banking industry tarnished in the public’s eyes by poor performance, excessive pay and the ongoing need for state support. Just where does the industry go from here and how does it start to rebuild trust, asks Anthony Duffy of Fujitsu UKI.
Banks might start by looking at their business with fresh eyes. True revenue opportunities must be taken while costs continue to be carefully managed. The customer relationship must be revisited, with banks considering whether the client management strategies of yesterday will work so well tomorrow. Banks might also recognise that they sit on a vast amount of information which – if only if could be easily accessed and cost-effectively managed – could provide new insights and new opportunities, both for them and their clients.
Despite the significant advances that banks have made elsewhere in their operations, relatively little use has been made of information contained in their own databases. This is set to change, as the volume of data created and collected accelerates significantly – some estimates suggest a sevenfold increase before the end of the decade.
Traditionally, many banks have tended to build bespoke IT systems. However, this comes at a cost – in terms of time, money and other resources. Yet growing interest in Big Data means that things might soon change. Thomson Reuters estimates that, in 2011, venture firms invested almost $2.5 billion in organisations focused on Big Data, up from $1.5 billion in 2010. Much of this money went into the four key components of any Big Data strategy: the storage and network services that support Big Data platforms; the platforms themselves, which enable data to be analysed; and the software applications that make sense of it – be it apps that enable large volumes of information to be processed or those data-driven apps that provide further, detailed insight. The consequence of this is that more “off the shelf” solutions are becoming available and the cost of storing and analysing data is falling – meaning that the opportunity to maximise the Big Data opportunity is now coming within reach of much more of the financial services industry.
The value of Big Data to the retail banking industry is estimated at more than £6 billion over the next five years. Immediate cost-reduction opportunities lie in fraud and sanctions management, while account management can be enhanced by enhanced customer insight. Taking a longer-term view offers banks the potential of significant new revenue streams.
Fraud is estimated to cost the UK banking industry around £1.5 billion per year. Within this, mortgage fraud runs at around £1 billion and plastic card fraud at about £340 million. In the Big Data world, spotting the relatively small number of fraudulent transactions in a sea of legitimate payments becomes less difficult, despite the sizeable shift in behavioural patterns towards electronic and mobile/internet payments.
Checking customers’ names against a sanctions blacklist can become highly complicated in a world where a bank has multiple customers with the same or a similar name. Each search runs the risk of flagging a false positive, thus embarrassing the bank and ruining an otherwise strong client relationship. By using Big Data techniques, this reputational risk can be mitigated and managed.
Big Data can also be used to enhance account and relationship management. By co-ordinating the collection of data already in the public domain – such as share price movements, a change in auditors or a director selling shares in his company – and passing it to account teams, understanding of key client businesses can be improved. Further insights can be derived from additional internal data, perhaps focussed around the early identification of potential problems – for example, how credit lines are being used against agreed limits; to monitor account crediting behaviours, as problem accounts often credit funds late in the day; and to identify payments patterns of potential interest.
One of the most exciting areas for Big Data lies in the potential to create new income streams for banks. By being located at the centre of the “payments web”, banks have unique insight into how, where, with whom and when customers are spending money. By analysing such information, banks can build an insight into customer intelligence and behaviours that they may well be able to monetise. Current examples of such innovation include:
■ an Australian bank is working with a retailer with to understand where the retailers’ customers live; when and where they shop; and how much they spend. This information is then used to refine the retailer’s branch location/relocation strategy;
■ an American payments company is partnering with a retailer to send discount offers to cardholders who use their cards in the vicinity of the retailer’s stores;
■ a Japanese mobile ‘phone network is partnering with a fast-food restaurant to send e-vouchers to customers who use their ‘phone to pay for food. Each e-voucher entitles the customer to a discount the next time they buy a meal in the restaurant.
Of course, the value and potential of the payments business has not gone unnoticed by others. In the first three quarters of 2012, Facebook made more than half a billion dollars from its global payments activities1, while PayPal customers used its service to make more than six million payments per day in Q3 2012 alone. And they’re unlikely to stop there. So another challenge for banks is to defend the payments business, both to protect their historic investment and to maximise access to valuable customer data.
At Fujitsu, we are seeing banks increasingly recognising the current and potential value of their business data – not least in informing ways by which the customer relationship might be “reset”. But many are daunted by difficult decisions around which high-performing IT infrastructure to select; finding and managing the highly-skilled, knowledgeable and data-aware personnel required; and funding Big Data initiatives, both in terms of money are other scare resources. These are no small challenges. But we are confident that the potential rewards offered by a successful implementation justify the effort.
Anthony Duffy is director of retail banking at Fujitsu UK & Ireland