Digitalisation has increased customer expectations in relation to the level of personalisation they receive. Whilst all industries regularly state that delivering a great customer experience is high up on their list of priorities, in many cases, there remains a gap between what financial services (FS) firms offer, and what their clients expect. 

The challenge for FS firms is that these expectations are coming from outside the industry. Think about the service you receive from online fashion retailers. Having visited their site once before, it will remember this and direct you to the department you normally look, along with tailoring the content you see, based on preferences and cookies. Last time you logged onto your bank did you receive a personalised service? It is unlikely, although some banks are making good headway, but the point remains that a one size fits all approach to digital journeys no longer works. This is not made any easier by restrictive legacy systems. 

Banks hold vast amounts of data, all of which can be harvested, and meaningfully translated to create an individual and personal experience. This insight, if deployed at the right time, with emotional intelligence, can enhance the customer relationship. Using predictive analytics and what is already known from transaction data can be made relevant and useful. According to the research quoted below, most financial institutions rate themselves as just getting started on personalisation (Digital Banking Report 2016). 

Whilst customers may want personalisation of service, there is a need for banks to reassure customers that their data will be safe and used correctly at a time when in financial service providers is low. To add to this, customers now expect to be rewarded when sharing additional data with financial institutions.  

Artificial intelligence and machine learning are now making it possible for organisations to process vast amounts of data and make a decision about what is best to show the customer. No longer should we be encouraged to open a new credit card, when we already have that credit card. This means a move away from traditional rules-based approaches to machine learning based algorithms.  

The end objective for personalisation should be a consistent, tailored experience across all channels, enabling customers to pick up where they left off - be it on an app, in branch, on a website or via a chat-bot. To do this, you need to be able to recognise and integrate your channels to understand your customers' interactions and behaviour. You then need to be able to interpret this behaviour with the data you already store in real-time and present it back to the customer in an individual experience.