How AI has transformed payment routing

It’s not a secret that AI is reshaping the payments landscape, playing a pivotal role in fraud prevention, regulatory compliance, and enhancing customer experience. One of AI’s most transformative impacts in the payments industry is payment routing, which ensures each transaction finds the most efficient and secure path from customer to the acquiring bank.

When a customer hits “pay,” the routing process automatically triggers, dynamically selecting the optimal pathway for each transaction. This choice is guided by fluid and static data, such as time of day, card issuing information, value, and risk factors, ensuring fast, reliable, and cost-effective payments.

Before payment orchestration was powered by machine learning systems, routing payments were managed by individuals, who relied on manual configuration to create blanket rule strategies for thousands of transactions. Since routing was not bespoke to each transaction and its associated data, optimising success rates was limited to human capability of analysing historical trends to create inadequate strategies, as well as being subject to delays and errors. Payment failures were often unpredictable and hard to manage, resulting in frustration for merchants and customers.

The integration of AI has transformed payment routing into a dynamic, intelligent, and highly adaptive process. This shift enables payments to be routed in real-time without human intervention and with remarkable efficiency and accuracy, selecting the optimal path in just milliseconds. The process is possible through an intelligent multi-stage system:

1. Payment received: When the transaction and its associated data hit a payment API, they are passed through data pipelines that calculate the probability of the transaction being accepted by each available acquirer, as well as the associated costs of each route. This happens in real time, based on the unique data associated with the transaction and the system’s trained model, which understands each acquirer’s acceptance nuances in unprecedented detail.
2. Routing instructions: After the acceptance rate of the transaction is calculated for each acquirer, the system lists the acquirers in order of highest probability of success and sends instructions for the top acquirers to the routing engine, which then routes and cascades the payment as needed.

Benefits of AI-based systems

Through this highly dynamic AI based system, merchants gain significant advantages for their business. For example, improved acceptance rates are one of the most important benefits to merchants, as more of their users’ payments are successfully completed. When using a machine learning acquirer acceptance probability model, the number of declined transactions decreases significantly, leading to an overall improvement in success rates.

Additionally, an AI-driven routing system facilitates access to more acquirers by dynamically managing and optimising the selection of acquirers based on real-time factors. This automation enables merchants to integrate and use an unlimited number of acquirers without the need for manual adjustments, making it easier to scale and maintain a diverse acquirer network.

Cost reduction is another advantage, as an advanced algorithm considers factors such as interchange and scheme fees, customised client and acquirer pricing, and any additional third-party costs. By calculating these variables in real-time, the system identifies the most cost-effective route without compromising acceptance rates beyond client-defined thresholds. This sophisticated approach ensures that merchants achieve the lowest cost route if that is their goal.

Moreover, enhanced customer experience is achieved through AI-driven payment routing that minimises payment failures and speeds up transaction processing, delivering a seamless, frustration-free experience for customers. By prioritising trusted or high-value customers, AI can further accelerate transactions, ensuring faster completions and a smoother payment journey for those who matter most.

Lastly, continuous improvement is a powerful feature of an AI-driven payment routing system, which learns continuously from past outcomes. Every successful or unsuccessful transaction provides valuable data that refines the model’s predictions for future routing decisions. For instance, if a transaction fails on a previously reliable processor due to a technical issue, the system will note this failure and adjust its model to avoid routing payments through that processor in similar circumstances in the future. This ongoing feedback loop ensures that the system becomes smarter over time, enhancing its ability to make optimal routing decisions and reducing the likelihood of payment failures.

Looking ahead

The pace of change shows no sign of slowing, and AI/ML offers ample room for further enhancements in payment routing. At the leading edge of development are systems that offer real-time routing strategies that adapt to shifts in acquirer behaviour, transaction patterns, and regulatory landscapes, as well as highly predictive engines that analyse vast datasets, including post-authorisation insights, to dynamically identify the optimal route for each transaction, maximising both speed and success. 

ML models will fuel many other advancements, payment tech innovators like Paytently, are looking at cost optimisation that will extend beyond basic fee structures, balancing intricate variables like currency exchange trends, alternative payment method efficiencies, and even blockchain speed predictions to pinpoint the most cost-effective paths in real time.

Behavioural biometrics and advanced diagnostics will further elevate security and resilience on cashiers and hosted payment pages, detecting potential fraud through subtle user behaviour patterns and enabling instant, autonomous correction of system irregularities. For payment professionals, AI-driven payment routing remains a frontier rich with potential for innovation and optimisation, making it an incredibly exciting moment to shape the future of payments.