Why finance firms need to big up big data
- 21 July 2015
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How customer insight is gaining momentum in the financial services sector
It is in retail that big data analytics have been most successful, helping brands communicate in a more targeted and personalised way with their customers. Take Amazon as one of the best examples.
But this data-led approach to insight is now spreading throughout other sectors, including financial services – and encouraging challenges from outside the traditional financial services sector too.
In an interview earlier this year with the Financial Times, Santander chairman Ana Botín identified tech giants Apple, Facebook, Amazon and Google as genuine threats to banks, a sentiment echoed by more than a third of retail bankers surveyed in a recent Economist Intelligence Unit report.
‘Banks are feeling the heat from competitors new to the world of banking who are capitalising on rapid advances in technology and fast-changing customer behaviour to launch innovative, data-driven business models,’ explains Ben Robinson, chief strategy and marketing officer for Temenos, a leading banking software company. ‘Increasingly, banks will be defined by the user experience that they offer discerning clients and data is playing an increasingly integral role in delivering this differentiated experience.’
In the UK, this trend started in the consumer banking sector. For example, Santander and Lloyds Banking Group are among banks that have teamed up with retailers to offer personalised discounts to customers via mobile apps, based on spending data.
This shift to being more customer-focused requires changes in approach, not only in technology, but also processes, culture and mind-set. Robinson continues, ‘To gain competitive edge, banks must seize the opportunity to become more involved in customers’ commercial and financial lives, analysing their transactional data to provide them with expert advice, find ways for them to save money and proactively recommend products and services they actually need.
‘The most successful companies will be those that are able to marry this analysis with analysis of customers’ locational and contextual information, to be able to deliver the right products, personalised to individual customers’ circumstances, at the right time and over the right channel – what we are calling experience-driven banking.’
The big idea
Big data covers large volumes of structured, semi-structured and unstructured information from a wide variety of sources – both internal and external. This ranges from demographic and psychographic information about consumers to online comment and reviews, plus social media, blogs, locational information from mobile devices and data from other connected IT devices. Research from EMC suggests the volume of data generated globally doubles every two years and, with the ‘Internet of Things’ emerging, this exponential growth will only accelerate. The challenge is how to ensure that this enormous volume of disparate information generates useful, deep intelligence.
Financial institutions have often had a uniquely intimate relationship with their customers. In the UK, research suggests that you’re more likely to stay longer with your bank than with your marriage partner – a familiar statistic often used to illustrate the inertia of consumers to change their current accounts.
But flip that idea around from the perspective of financial services organisations and it’s clear that they have a deep mine of long-term customer data – including transactional behaviour, changes in personal and business circumstances and, of course, relationship history. When it comes to utilising consumer data, this is about more than just which brand of baked beans or washing powder a customer prefers.
But where competitive advantage increasingly lies for financial services is well beyond managing sources of internally-generated data. The big data revolution has upped the ante for all kinds of enterprises. In an ever-more interconnected world, it is becoming easier – and cost-effective – for organisations to access massive datasets from many places.
Combined with an increase in computer processing power and sophisticated software tools, this unlocks the potential for organisations to search and analyse the information to identify and explain trends, gain detailed, more valuable insights into consumer behaviour – and to use analytics to look into the future.
The financial services industry stores vast amounts of customer data – and tougher, new regulatory supervision and compliance regimes are adding to this. Organisations’ conventional data management function has, arguably, shaped the mindset and approach to harvesting data, with this massive store often held in different locations, in a variety of formats and on diverse technology platforms. Before the big data revolution, harnessing this would have entailed a huge commitment of resources, with business value difficult to quantify.
That has influenced the big data debate for some. ‘While predictive analytics helps in identifying futuristic aspects and what one needs to do with it, implementing such recommendations was challenging as, in many situations, it was leading into process changes within financial institutions,’ says Soumendra Mohanty, vice-president, global data and analytics practice at IT consulting firm Mindtree.
However, new powerful analytical software tools are opening up opportunities to use the wealth of data in meaningful and innovative ways. Businesses can gain a clearer insight into customers, understand their needs, be responsive to trends – and predict future business needs.
The use of big data isn’t just a technological solution, though. It should be seen as an asset to be used as part of an ongoing integrated business development and IT strategy, prompting new questions to be asked, and encouraging creativity and fresh thinking from management, analysts and IT.
As the market becomes ever-more competitive for financial services organisations, embracing big data is no longer optional – if you’re not doing it, your competitors, both new and old, certainly will be.
Why big data is relevant to everyone:
- Big data analytics can help you use conventional and unconventional data from many sources to discover deep insights into your customers’ behaviour, understand market trends and predict future patterns.
- Harnessing the power of big data analytics can help your organisation improve the customer experience; strengthen marketing; help create new business areas; improve operational efficiencies; and be more competitive.
- Big data analytics is more than a technology solution – it should be part of your overall integrated business development and IT strategy. To be effective, it requires well-planned analytical processes, the right skills and talents, an innovative, agile approach and creative thinking.
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