A Manifesto for How Retail Banks will Survive and Thrive in 2017
Banks constantly look over their shoulders at other banks.
When one makes a new move, the others quickly follow and imitate. Keeping an eye on the competition makes sense, but the lesson for the banks in 2017 is to be even more fixated on what customers really desire. This does mean radical change. For example, banks have seen their investment in fintech as about reducing the time for payment processes; yet customers want to eliminate the time taken entirely.
Taking a customer-first philosophy is about being realistic about customers’ motivations. Banks pursue the idea of loyalty and trust, but these values are not as important to today’s consumers compared to a generation ago. Banks should treat customers as serial transactors that do so as it fits their level of convenience, with no obligation towards the bank. The reality is tough for banks but acknowledging it does give them something to build on, rather than the conflicted situation in which banks find themselves today, i.e. as long-established institutions offering stability and services to everybody, that also are pressed to be more innovative, fast moving and customer-friendly (a situation exacerbated by successive governments’ oscillation between seeing banks as lepers, the cutting edge of the services economy, and instruments of social change).
Do something with the data
For banks there is an existential challenge that must be faced in 2017 (indeed should have been faced in 2012, 2013, 2014, 2015 and 2016). Banks see themselves as destinations physically on the High Street or online, yet consumers view them as simply components in a wider value chain. Nonetheless, banks still view themselves as important institutions and central to people’s lives. They need to break with tradition and pursue new models that focus on outcomes rather than process or tradition, and add value to how they help customers transact.
Quite simply, banks should become predictive forces in their customers’ lives. They have an incredible wealth of data on customers – spending habits, credit, lifestyle choices – and banks must leverage this more effectively to offer customers truly personalised, attractive services with offers and co-branding initiatives that are demonstrably valuable, rather than incidental to customers.
To date, banks have ‘sort of’ recognised this opportunity, but have been slow to do anything. The gamechangers they cannot ignore are the latest artificial intelligence technologies. These can be properly melded with a customer relationship and engagement management system to give banks an always-on predictive analytics to see, select and act on insights quickly and accurately. Combined with robotic process automation, banks can be responsive at speeds customers desire and create the space to re-invent and personalise services.
Analysing and acting upon more customer data in real time and context helps a bank manage risks more creatively and accurately, and begin to break the mould of how they create services. Some of the offerings that banks might weigh up in 2017 and beyond are:
- ‘Lifetime value’ calculations would need recalibrating with a longer maturity period and expectations of higher promiscuity or customer disloyalty. This is likely to apply as much to the much-vaunted Millennials as to the Baby boomers who are entering their sixth decade of work or becoming the new retirees
- Nature of property lending to younger people is going to need to change to reflect their graduate debt, e.g. with products that comprise a partial shared equity deal rather than purely deposit + mortgage and even ‘mortgage swaps’ between a part-owner who wants to move out and their ‘replacement’. The equity might well come from crowdfunding, perhaps including monies from people building for their own purchase
- Creating services that are sensitive to an aging customer base will become more important. Significant financial decisions are being made in later life, such as what to do with pension pots or HIT-vulnerable wealth. This requires banks to offer complex advisory services to a growing market and explore ways of moving funds through generations or ‘good causes’ without losing control/benefit during the redistributor’s lifetime. AI and machine learning can help staff to guide customers through these significant decisions.