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Real-time payments and the transformation of bank business models

Payments are the backbone of every bank – it is a fundamental activity of which 100 billion in wholesale payment transactions annually generate $262 billion in fee and balance revenues. The current generation of bank payments has been around for a long time – in fact, their design dates from Victorian times when payments were, at best, a next-day affair. Customers walked into bank branches, filled out an order to pay, and the bank would process the payment the next day by debiting the client’s account and forwarding the money to a named beneficiary. Fast forward to today and client needs have changed dramatically. They expect an utterly different experience – a frictionless, omni-channel experience enriched by data and integrated into the ecosystem where they transact.

Upgrading core payment systems is a necessity for modern banks

To state the obvious, the payments playing field is no longer level for banks processing on batch-oriented legacy mainframe systems. The rise of fintech firms, the shift in consumer habits and demands, the advent of our data economy, and the arrival of multiple new technologies in financial services have dramatically altered the landscape. The publishing of so many new banking and payment APIs is evidence of the shift in business model orientation to a more open economy where payments are integrated into wider, “‘one-to-many” ecosystems.

Keeping pace with these challenges is forcing banks to modernize their platform to improve agility and significantly lower the cost of managing old systems. These new systems – modern data centers and cloud-based technologies – empower banks to meet customer expectations for fast, anytime and anywhere service, while enabling banks to future-proof themselves to accommodate the increasing velocity of new requirements.

Real-time payments (RTP) drive innovation

RTP isn’t just payments, it’s about the data that travels through bank payment systems in real-time, day-in and day-out. Embedded in this data are valuable insights in to clients and their banks in terms of cash flow forecasts, sources of liquidity, and counterparty risks. Understanding the behavior of these financial flows form the heart of accurate management of the working capital cycle for businesses. Supply chains are a complex mixture of real-time logistics and payment flows that minimize risk and maximize liquidity management. Banks play a central role in these flows, but historically have done little to understand the data, its context, and how clients could use these insights to improve their businesses.

Until now, the use of this RTP data pipeline was limited to static reports on client activity such as the Swift MT940’s treasury dashboard displays and reconciliation services. Today, cloud-based tools interpret data in real-time – something humans could not do given the volumes and velocity of the data – making artificial intelligence, machine learning, and contextual services indispensable tools. By understanding the relationships between data points, historical patterns can be used to predict upcoming events and interpret the context of payment flows. Banks are also gearing up for the potential new business models and products that the data flows could unlock. Because of this, data science is becoming a crucial product management vocation within bank Cash Management lines of business.

The industry has taken note of this real-time potential. ClearBank, the first new clearing bank in the UK in the past 250 years, delivers flexibility, speed, and security to their customers. ClearBank partnered with Microsoft to enable RTP, providing customers with instant access to transactions—while enhancing security thanks to Microsoft’s deep investment in cloud security. With an integration period of only 8 weeks ClearBank offers customers instant service hosted on a platform with maximum security.