The mobility trend that began with smart phones is rapidly expanding with the proliferation of connected devices. Distribution channels as we once knew them are growing to include connected devices, creating new opportunities. Cars are already internet enabled - several already integrate to iTunes. It’s only a matter of time before you can access a banking app like goMoney from your car using voice commands.
Digital Natives want to be able to program their thermostat - and connect to it over the cloud to check the heating is on. Data Natives want the thermostat to be intelligent - to learn how warm they like each room in Summer and Winter. And optimise these preferences to reduce their energy bill.
Digital natives might use a cloud-connected baby monitor. Data natives expect their monitor to calculate crying percentiles based on data from millions of other babies and know the difference between babies murmuring in their sleep and babies in distress or in need of attention.
Digital enables connectivity. Data makes it useful. Data native customers have much higher expectations of organisations.
As a bank we are working on new capabilities that build a “sense and respond” capability across all of our channels. Our aim is to be continually scanning for customer events and to be able to understand the context, formulate a decision and deliver the right response, all integrated into our operational systems and tailored to the customer across any channel or device.
A simple example might be identifying when a high value customer has received an unexpected bill and is about to have their card declined. We need to be able to make a split second decision whether we contact the customer, requesting approval to transfer funds between accounts to enable the transaction.
Responding to expectations of data native customers requires significant changes not just to technology but also to business processes and our culture. Our platforms are becoming more integrated with a streamlined flow of information managed by context aware decision engines. And we are shifting our culture to consider new processes and new skills and capabilities.
Trust has always been a key currency for banks but customers have different attitudes to privacy and protecting their data. One of the most popular free apps before it came as standard issue with your phone was the flashlight app – which merely enabled your camera flash. In exchange for downloading the app for free, rather than pay $5 for it, users had to provide their geo-location all day long without any notion of who would get this data or what they would do with it.
Non-traditional competitors – such as merchant acquirers, supermarkets and peer-to-peer lending – offer similar products and services to banks and are influencing customer expectations and changing our industry.
Mobility and wearables offer companies and individuals unique insights into consumer behavior. The likes of fitbit and jawbone offer insights into your health and will in time provide data for insurance policies. Disney’s MagicBands – like magic beans but they grow data, represent a billion dollar investment by Disney. They are individually coded to each visitor and allow Disney to track individuals wherever they go in their resorts. MagicBands let you check into rides, skip longer lines, pay for purchases and open your Disney hotel room.
The pitch that Disney is making is personalisation but the insights and data that they will get for models on itineraries, line length and weather will help them figure out what influences length of stay and cash expenditure and these have big prizes attached.
Expectations are higher
Sales and service experiences are measured against Apple, Google and Amazon not against other banks and retailers. But trust is a key advantage for banks and we need to find ways to demonstrate to customers we protect their data and use the information to add value back to them. With trust, customers can be persuaded to share more data with you, as long as they see the benefits.
The skill shortage
Addressing the skills gap will be one of our toughest challenges. We need new capabilities such as anthropologists, behavioural scientists and psychologists working alongside bankers, data scientists and software developers. It will be challenging to hire and retain these people in a ‘traditional’ banking culture – and that means that we need to adapt our culture to be successful.
Next generation analytics moves the focus away from managing data – organising and understanding it, to using and applying it in a contextual way. It’s what you do with the data that creates the value.
We need to bring new capabilities together into an eco-system. It’s not about predictive models but highly personalised content that creates relevant conversations with our customers. We are informed by new types of data – like video or tone of voice, that pick up on key behavourial signals, and we need to create systems that continually adapt and self-learn.