By Parth Desai, Founder and CEO, Pelican
To win and retain customers, you need to understand them in detail and to serve their individual needs.. To do this effectively you need data and the ability to understand and interpret that data to build ‘customer cognisance’. In this blog, I’ll explain three key steps that are essential in achieving this.
Innovation in relation to Open Banking and PSD2 has remained pretty steady over recent months despite the impact of COVID-19. As can be seen on the Open Banking app store launched by the UK's Open Banking Implementation Entity (OBIE) in June, the range of apps and online products available to consumers and businesses is alredy quite extensive. But whether the apps on offer are from new fintech entrants or established financial institutions, most have one thing in common: a focus on customer-centricity.
To win and retain customers, you need to understand them in detail and to serve their individual needs. As customers become more aware of the nuanced and tailored services they can access through Open Banking, it’s no longer engouh to group them into demographic types or segments that you can target en masse. To do this effectively you need data and the ability to understand and interpret that data to build ‘customer cognisance’. Here I’ll explain three key steps that are essential in achieving this.
1. Use data and AI to build customer cognisance
In the past, banks have done relatively little to understand the vast amount of customer account and transaction data they hold. For banks to thrive in this era of change, they need to view Open Banking as an opportunity to truly understand the needs of their clients – both personal and corporate. They should not underestimate the value and volume of data they hold, and its potential to provide hugely valuable insight into customers’ financial habits, interests and needs.
If the customer chooses to share this data with trusted third parties through Open Banking protocols, then these authoritative records of everything spent, lent or borrowed, when, where and to whom, will be available to innovative and dynamic new players. Incumbent banking services will be vulnerable to the new products and services that are able to leverage and aggregate this huge amount of cross-domain data.
So what should banks be doing to build customer cognisance? If current systems fail to adequately reason over existing data repositories that are largely unexplored, siloed and passive, how will the bank cope with any additional, and potentially sizeable data sets provided through Open Banking, given with consent from outside the bank? How can they understand exponentially greater volumes of often unstructured and unformatted data?
Here Artificial Intelligence (AI) and the related disciplines of Machine Learning (ML) and Natural Language Processing (NLP) are essential. It’s only through AI that extensive customer data sets can be transformed into actionable business insight and intelligence. awareness, or cognisance of their customers: the ability to analyse data and truly understand customer needs.
2. Offer personalised customer-centric services
Once banks have the insight in place, they can then develop the truly customer-centric services that are rapidly becoming the norm. The ability to translate customer data into meaningful, enhancing and hyper personalised services and benefits to customers will be the true differentiator between businesses that thrive and those that struggle. For banks, transforming insight into beneficial services and products must become a primary focus.
While there will be many different approaches and innovations, leveraging AI disciplines will be an essential business enabler. There’s no question that making sense of the data available in order to design personalised services that engage customers at scale requires AI.
3. Engage consistently across multiple channels
Banks need to adopt the capabilities required to engage with customers across the wide range of intelligent platforms and ambient devices consumers and businesses increasingly rely on, utilising voice and other emerging interfaces. Again, it will be through the deployment of AI disciplines that these highly customer-centric, truly engaging service capabilities can be deployed and communicated to customers. Such systems involve voice recognition, natural language processing, context management, machine learning, rule-based heuristic processing, all combined and working in sync. Again, delivering a fully integrated and intelligent approach across a full range of touch points and channels will require AI.
What’s more it will be essential for banks to capture activity and feedback gained from customers through all channels and to proactively use that data in building a more holistic view of the customer, their preferences and behaviour, enabling ongoing continuous improvement and more personalised service.
How banks develop and deploy such capabilities is a strategic question and one that will almost certainly involve collaborating with proven fintech partners – ones that have both a technology and payments domain pedigree.
In today’s hugely transformative environment, a business-as-usual approach is simply not a viable option if banks wish to remain relevant and to prosper. To me it’s clear that leveraging the powerful capabilities of AI-based technologies must be at the heart of any successful Open Banking strategy.