BANKING ON WILL BIG DATA TRANSFORM THE CUSTOMER EXPERIENCE? A Retail Banking perspective

BANKING ON WILL BIG DATA TRANSFORM THE CUSTOMER EXPERIENCE? A Retail Banking perspective

Big data provides an opportunity to deliver exceptional customer experiences and competitive advantage in an industry still struggling after the worldwide financial crisis. TRANSFORM, 2015 BANKING ON As the Financial Services industry becomes more digitally enabled the amount of data collected increases. The industry could be sitting on a virtual data goldmine. The questions that we re exploring in this paper are whether: 1 the industry is positioned to take full advantage of this WILL BIG DATA TRANSFORM THE CUSTOMER EXPERIENCE? A Retail Banking perspective 2 this will be used to benefit the providers, used to transform the customer experience or both

1 THE ROLE OF BANKING IS CHANGING Banks have traditionally focused on keeping money secure and enabling customers to transact. Whilst this remains a key tenet of the proposition, the rules are changing and in an increasingly competitive environment banks are being forced to differentiate themselves. Big Data has the potential to unlock latent value that will move banking from becoming a utility to a provider of value added services. The range of potential services is vast: improving and making the internal operations more efficient through to providing value to customers at each stage of the customer lifecycle, from sales all the way through to service. And the good news is that the cycle is virtuous; the more data that is collected and analysed the greater the value that can be added. This is not to say that banks haven t been using data effectively already. They have. But it has largely been for internal benefit. Decisions around fraud and internal risk management have been made on big data sets but even in this space new data sources are changing the rules too. For example, Biocatch provides fraud management software that proactively collects and analyses more than 400 bio-behavioural, cognitive and physiological parameters to generate a unique user profile and help assess security risk. Banks now face the challenge of how to use the growing quantity and types of data for propositions that create value for customers. The volume of data captured in today s digital and increasingly cashless world is growing at a rapid pace. Combined with the falling costs of storage, data is fast becoming one of the banks biggest assets. But the volume and types of data also provide challenges in organisations that were not originally designed to analyse data of this scale and complexity. The real challenge is how to turn the data into insight to transform the business and customer experience. According to IDC s December 2012 report - The Digital Universe in 2020 only an estimated 3% of global data is tagged and less than 0.5% is analysed. Banks are now able to access structured data like value, currency and transaction type as well unstructured data like location or social media comments. Therefore, there s a need to capture, merge and analyse data sets using evolving data science methods that enable interpretation and drive action. Creating value for customers as well as driving better risk decisions

A few examples: Ask consumers what they receive from their bank and the response is most likely to be irrelevant information about products I don t need or already have. This is despite the fact that most banks now have access to data that, if analysed correctly, would undoubtedly lead to different decisions being made. How often have you been sent unsolicited marketing material from your primary bank encouraging you to take out a loan, despite you holding a healthy balance in your savings account? FICO s 2015 report on the banking habits of millenials claims that ~46% of households receive irrelevant offers. Another routine example is those customers that regularly go overdrawn on their accounts at certain points in the month resulting in unauthorised overdraft charges. Alerting functionality has been rolled out to help customers avoid and react to this situation, but the banks have benefited from collecting revenues from customers struggling to manage their cash flow. So if banks have been sitting on data that could have been used to accurately predict when a customer is likely to go overdrawn where s the incentive for them to share this insight? Transform s own research into the digital maturity of 150 organisations [DMI 2014] has revealed that there is a clear split between those companies that use data and insight to add value to customers and those that don t. With banks and other financial services providers holding a considerable amount of data on their customers they have the opportunity to provide personal BUSINESS VIEW Do you currently utilise customer data and insight to provide value added services to your customers? 57% 43% NO YES financial management information and partner with brands to provide special offers based on spending patterns subject to regulations. The consumer view is split on this approach possibly because personalisation is typically limited to the offer of additional products rather than value added services. To what extent do you agree with the following statement? My bank provides me with a personalised service based on what it knows about me? 46% of households receive irrelevant offers 40% CONSUMER VIEW AGREE DISAGREE 11% 3% 35% 11% Turning the abundance of data into actionable insight

Other industries have been quicker to recognise the opportunity that big data presents and there are lessons that can be learnt and applied to banking. The following highlight a number of industries that use data on a large scale to the advantage of the organisation and its customers. Tesco Clubcard driving loyalty through personalised offers Following a successful trial in 1994, Dunnhumby helped establish a new loyalty card, Tesco Clubcard. Famously commenting on the trial, Tesco s then Chairman Lord MacLaurin said What scares me about this is that you know more about my customers after three months than I know after 30 years. Clubcard became a key asset in Tesco s armoury, collecting and analysing data on the shopping habits of millions of customers and providing personalised rewards to tempt customers to buy more and to drive loyalty. That said, whilst it s widely acknowledged that Tesco Clubcard was one of the most important retail innovations of the 20th century, some commentators also believe that the way Tesco is using the data is in need of a complete overhaul. The offer based promotional approach has been superseded by a more straight forward pricing strategy offered by some of its competitors. The key take-away here is that the value is not in collecting the data, nor in the analysis but what you do with it. Amazon mass personalisation With data collection and analysis firmly established within the DNA of the business across all functions, Amazon has been using data to drive better customer experiences and operational service excellence. In fact, Amazon has become the poster child for developing a customer-centric business without so much as talking to customers. It has managed to create personal relationships in an automated way and even to the extent of anticipating customer needs. The business has also been able to adopt a data led strategy to proposition development such that new propositions are launched first, then measured and assessed with real customers on the live site. Banks have traditionally ignored the potential insight often leading to poor customer experiences

2 SO WHERE DOES THE OPPORTUNITY EXIST FOR BANKS? Not only are banks sitting on huge amounts of data that can be used to serve customers in more relevant and engaging ways, there is also an opportunity to strategically shape the business through reliable factual insight. The more progressive banks are beginning to deploy big data analytics to yield results around: UNDERSTANDING CUSTOMER BEHAVIOUR PREVENTING CRIME DELIVERING A MORE ENGAGING EXPERIENCE INCREASING LOYALTY AND ACQUISITION DRIVING IMPROVEMENTS IN COMMERCIAL PERFORMANCE CREATING NEW PROPOSITIONS THAT PROVIDE A BETTER VALUE EXCHANGE Value is not in collecting the data, nor in the analysis but what you do with it

WHAT OPPORTUNITIES COULD BIG DATA OFFER RETAIL BANKS? Intelligent Marketing & Sales Through intelligent application of (real time) customer and market insight, the banks will be able to market in a more targeted and personalised way. Building in an understanding of what I have been looking at, the time of day and my location the bank is in a powerful position to offer me (the customer) something that I really want. Banks will be able to engage with customers around products and services that will be well received and based on need rather than what the organisation wants to sell. And marketing ceases to be purely about generating leads and instead becomes a value added customer service. It may seem a little far-fetched, but imagine a future where my bank recognises that I am standing in a car showroom whilst looking at loans on my mobile phone. Could my bank make an instant loan decision based on knowledge of who I am, together with a photo of the car registration number? Personalised Pricing Since its origins banking has relied on strong risk management policies and procedures. Customers who are considered more likely to default are deemed a higher risk and will be charged a higher premium for products and services. On the flipside, those with a good track record and a strong credit history can be charged a lower premium. Some banks are already tapping into unlikely sources of data that provide an indication of risk. For example, Satsuma, the consumer loans business Provident Financial, has launched a decision engine that offers the ability to interrogate behavioural and social data for use in credit decisioning. Imagine a reality whereby your bank taps into your social network (e.g. Facebook) to assess the likelihood of you defaulting and providing personalised pricing based on this information. Behaviour change Perhaps the nirvana is using big data sets to provide predictive insights that enable banks to offer goods and services to customers in a preemptive manner and ultimately drive customers to change their behavior. Imagine if your bank could use data to: Provide pre-emptive warnings if I am about to go overdrawn Reward good financial behaviour (for example to encourage me to save 5 per extra per month or have one less Starbucks coffee a week) Provide tailored and specific advice (for example, recognising that I could use the money in my savings account to pay for my home insurance in one instalment rather than making monthly payments for which I pay a premium) Offer personal financial management tools to categorise and visualise my financial spending patterns Recognise my stage of life and offer products and services that match my needs Imagine if your bank could use data to reward good financial behaviour

3 WHAT ARE THE CHALLENGES AND WHO WILL WIN There is almost no industry better poised to profit from big data than the financial services industry. But the challenges are significant and numerous with the following providing the biggest concerns: Systems Existing banking systems were not designed to support the scale, variety, speed and complexity of data that can now be integrated with existing datasets and analysed. In order to overcome this in an effective manner, banks need to think differently about how they store, manage, integrate and analyse the data. Organisation Similarly the way that banks have traditionally been structured does not lend itself to them being able to take advantage of what big data can offer. New roles and skillsets are required including a new kind of professional the data scientist, who combines the skills of software programmer, statistician and storyteller/artist to extract the nuggets of gold hidden under mountains of data. Economist Data Data Everywhere, 2010. The organisation also needs to adapt to the reality that the data crosses internal silos. Customer Intimacy Although big data presents enormous opportunity, it also heralds an era of great risk for the banks. It is essential for banks to keep the data secure and use it in a fashion that is acceptable for their customers. There is a real risk of banks stepping over the mark and becoming a little creepy. It wasn t long ago when Visa was forced to deny that it had the capability to predict when a customer was going to get divorced, even before they did. So the traditional banks need to move fast to keep up with the pace of the new digital only challenger banks (for example Starling, Atom and Moven to name just a few), who don t have the legacy systems issues, the organisational constraints and have the permission to use data in a fair value exchange with their forward thinking customers. To continue the discussion further please contact James Goldhill at: E: james.goldhill@transformuk.com T: 0203 128 8018 James is Financial Services practice lead for Transform ABOUT TRANSFORM Transform is a specialist digital and multi-channel consultancy working with clients to deliver customer-centred change for commercial benefit. Over the last 15 years, we have been working at the forefront of the digital, multi-channel and customer experience agenda with clients including Argos, Debenhams and Homebase. In more recent years, we have begun to share our learnings from Retail and have developed a strong and growing FS practice to help the likes of Santander, HSBC, Barclays and Investec and more niche organisations like Zopa and Police Mutual on their digital journeys. Our work spans from digital, multi-channel strategy through to customer experience, IT architecture, prototyping and software development. James Goldhill, Head of Financial Services at Transform