Andrew Joss, head of solutions and data governance, Informatica
In this era of data-led business, where mobile apps, self-service banking and online information are the norm, the banking sector is undergoing a painful shift of focus. The banking establishment is having to change processes that have remained fundamentally unchanged for decades, handing more power to its customers and bending over backwards to accommodate their desires for availability, transparency and efficiency.
Banks, especially in the retail sector, are having to consider what their value proposition is across all their customer segments. Added to that, the reduction in brand loyalty and the rise of new intermediaries like Apple Pay means banks are under huge pressure to innovate and change to remain relevant.
Younger challenger banks are beginning to take away market share with a more customer-centric approach, with good data management at the heart of their strategy. Their tailored deals, extreme usability and ‘culture of comfort’ are pitched at a generation that’s grown up on Amazon and Netflix – the ‘now’ generation that wants to be made to feel special and known by the companies with which it interacts.
Digitally-savvy customers want to have all their banking information at their fingertips and don’t want to have to walk into a physical bank branch to perform everyday banking tasks like changing their address or adding a new savings account. It’s not just millennials who are bringing the expectation of personalisation into banking, either – Generation X have adopted a data-driven culture of the digital world just as much as their children.
Time to change
For the established high-street banks, this should be a call to action. The sands are shifting and a new, data-driven approach is needed if they are to retain the loyalty of their existing customer base and gain new customers. By ensuring they have deep insight into the data they hold and what it tells them about their customers, traditional banks have the potential to keep up with the rapid changes in their industry.
No bank is too big to fall, as we learnt in stark terms in 2008. The fourth industrial revolution won’t be as cataclysmic a shock as the Credit Crunch, but if financial institutions don’t make the most of their data assets they risk being left behind by more digitally-savvy competitors.
Steps to digital transformation
With this in mind, there are a number of key steps that banks should take to ensure they can continue to compete against nimbler challenger brands.
First, it’s essential to map your data landscape. Larger organisations may face a greater uphill climb to achieve the necessary data-driven digital transformation, but they also have the benefit of much larger data repositories. They have more customers and a longer history with them to call upon when driving personalisation and digitisation projects.
That can be a real benefit in terms of understanding customer behaviour and needs, but first you need to be able to understand what data you hold and where it resides. An automated data mapping project is a good place to start, speeding up the process of locating and identifying relevant data.
Once you’ve discovered the information you require, the next step is to integrate it in one place to make it easier to analyse. Most organisations’ data is spread across multiple systems, both in-cloud and on-premises, so an automated hybrid approach is often the best way to efficiently carry out this process.
With the right automated integration tools in place, financial institutions can centralise their relevant information into a data lake, where it can be made more easily available to business-related projects. Data cleansing should also form part of this process, removing irrelevant and outdated information to ensure that next generation analytics projects are working with the best data possible.
Analytics for customer-centricity
Once you’ve amassed your data, you need to start using it. Data analytics based on years of historical data provides established financial services companies with an opportunity to automate customer interaction and processes, as well as provide a better view of lending environments.
Data stores can be analysed to uncover actionable insights including borrowing trends, peak spending times, consumer responses to market shocks and the popularity of tools and services like online banking and mobile apps. When turned on external data it can also help banks to get a clearer picture of movements in the market and make informed assessments of upcoming challenges or opportunities. This new approach helps banks move from being a traditional service provider, to much more of a relationship partner; using data-driven insights to deeply understand the needs of their customers and deploy all their financial assets at the right time and in the right way.
In turn, this information can then be used to inform business plans, brand management, product launches and overall customer relationship strategies, helping financial institutions to match their activities and growth plans to what their current and future customers want. A data-led approach to banking also helps to generate an appearance of openness and relatability.
It’s important to treat customers as individuals, and for large multinational companies, the only way to truly do that is through effective, automated data analysis. Data is the key to understanding people as people rather than targets.
The future is data
Newer challenger banks don’t have an in-depth historical view of the customer, the housing market or the business lending space, and that gives more established financial players a huge opportunity to meet the growing demands of the ‘now’ generation. Now is the time to implement a powerful, high-capacity automated data management strategy to ensure that data stores can be accessed, analysed and put to use. A data-led approach can bring major dividends in terms of customer relationships and market intelligence, but it’s essential to have the right tools in place to make it happen.