However, this model has become unprofitable due to the cost of implementing new payments rails such as Real Time Payments (RTP), underlying infrastructure costs (hardware and software), and the need to reduce transaction fees in response to increased competition.

In addition, as Open Banking drives players towards a “platform-based” business model, the ability to partner and collaboratively build new business services quickly becomes an imperative that is not cost sustainable today. According to the report, these evolving requirements will not be met by existing transaction-led revenue models.

To offset the fall in payment profitability, Aite Group call for banks to use payments data to develop enhanced business services based on data-analytics that will open up new revenue streams and increases customer “stickiness”.

Banks should leverage data-driven revenue models that can monetise rich payments data through the delivery of new services and capabilities. These offerings range from enhanced account and transaction information to potentially pre-integrated into ERP, treasury management, and accounting systems.

For almost one in ten of the world’s top tier banks, however, this revenue model concept isn’t new. BBVA’s ‘PayStats’ offering provides anonymised and aggregated statistical data from millions of transactions performed with BBVA cards and any other cards used at BBVA POS terminals, creating a virtual map of consumers’ habits, demographics and origins for other companies to purchase. Square provide a similar capability to their merchant customers.

However, most banks are struggling to change revenue models. This is due to three factors:

1. Short-termism: Monetising payments data is a less important driver for change when compared to Real-time Payments. In the US, existing revenue streams from payment transactions mean that banks are reluctant to impact what is still perceived as a ‘cash cow’.
2. Complacency: ‘If it’s not broken, don’t fix it’ attitudes held by the banks. This is dangerous as the tipping point can come very suddenly – just like the “Kodak moment” – and fast, leaving too little time to react.
3. Guidance: Many other banks are aware that they need to use payment data and alter their revenue model, but don’t know how to transition.