1. Treating data as a strategic asset
The biggest obstacle for banks has always been the sheer difficulty of accessing the right data and in real time. Advancements in technology such as data fabric and cloud adoption have made this cheaper and easier.
As well as enabling technical access to payments data as a strategic asset, ownership, and governance of payments, and payments data specifically, must be put in place. This is essential to ensure that insight and ultimately value can be created, whilst also remaining compliant with obligations to protect data and manage appropriate consent for its use.
It should also be recognized that it’s not just about the payment data. Additional data from other sources, such as behavioral and location-based data, when combined with payments data will drive richer insights and contextual awareness. This ability to generate specific, targeted insights using large amounts of data from multiple complementary sources is what the Big Tech firms have excelled at.
2. Driving insights from data
The key thing banks can do with this wealth of data is to build a richer and deeper understanding of their customers, consumers, small businesses, and large corporates. The goal is to create hyper-personalized insights, specific to the circumstances of individual customers, allowing banks to engage in the moments that matter to customers – deepening relationships, and moving away from a more transactional approach based on ‘broad brush’ segmentation. Where appropriate, engagement with customers can also be done in real time, recognizing the time and place that is most convenient and relevant to customers, making contact more valuable for both customer and bank.
Banks can use third parties to accelerate this process. For example, banks looking for a richer and deeper understanding of customers’ needs and behaviors should seek a system, such as EY Nexus for banking to bring together data from across their operations. This allows banks to anticipate needs and create hyper-personalized experiences/services, fuelling new sources of growth. This could be used to support customers throughout the entire mortgage journey, from house-hunting to moving in – engaging in a way that recognizes their personal context and increases mortgage conversion; or enabling merchants to better understand and serve their own customers through real time insight generated from payments data.
Engaging with customers in this way delivers benefit for all parties – customers through more relevant, targeted products (no more ‘generic spam’) and banks through increased revenues from better conversion rates on existing products, and new revenue from additional insight-led services.
3. Driving value from insights
To turn these insights into revenues, banks can learn lessons from other industries. For example, the way digital entertainment platforms make recommendations and commission programs based on viewing data, and smartphones recommend apps based on location and time of day. Similarly, banks can use insight gleaned from payments and other data when designing new products and services, creating solutions tailored to meet customer needs.
The rich insight that payments data offers will also enable banks to improve their ability to cross-sell. Effective cross-selling is highly dependent on how well you know and anticipate customer needs. Payments data, and the behaviors it reflects, can significantly improve banks’ ability to understand customer needs, allowing them to identify the right product and offer it in the context of that need, at the right time, and in the right place. The data can also enable a better understanding of the relationships across local/regional economies, building a richer picture of connections and dependencies – using this to better anticipate business needs. This is illustrated by a rise in banks creating specific ‘data’ or insight-led products, targeted towards larger small to medium enterprises (SMEs) / corporate clients.
There is still an opportunity to go further, partnering with third parties to provide deeper insights into specific industries (e.g. Agriculture, Hospitality). Or creating new platforms to drive engagement and connections across business or consumers, informed by the connections inherent in payments data, further enriching their understanding of needs and behaviors.
To make the most of these opportunities to improve engagement, it is also necessary to deploy new commercial models, for example, consumption-based or subscription-based models for insight. For some firms, this will require a significant shift in commercial and operating models in some areas of the business.