Q&A: SmartStream’s Roland Brandli on AI’s transformative role in payments

Artificial Intelligence (AI) is reshaping industries worldwide, and the payments sector is no exception. While the buzz around AI often highlights its capabilities in predicting customer behaviour and personalising experiences, Roland Brandli, Strategy Director at SmartStream, supports that the real value of AI lies in more robust applications like fraud prevention and transaction efficiency.

As the global payments landscape evolves, the need for sophisticated, agile, and scalable solutions becomes paramount. AI stands at the forefront of this transformation, especially in the context of mobile and instant payments.

Recent data indicates a significant uptick in the adoption of mobile payments, with instant payment volumes tripling since 2020 and projected to rise at a compound annual growth rate (CAGR) of 16.7% from 2023 to 2028. Regions such as India, Brazil, and Asia Pacific are leading this growth, underscoring the necessity for advanced AI-driven technologies to manage the increasing volume and complexity of transactions.

In this discussion, Brandli explains how AI can improve transparency and efficiency within global payment systems, contribute to anti-fraud measures, and support financial inclusion initiatives. He also addresses the foundational requirements for effective AI implementation, the potential limitations of generative AI in operational contexts, and the critical importance of high-quality data in driving AI success.

Q1: AI is a hot topic in many industries, including payments. What are your thoughts on its potential and value?

Absolutely, AI is generating a lot of buzz, especially in the payments sector. However, the real value lies beyond the hype. Over the past few years, there’s been much talk about banks leveraging AI to identify customer buying behaviours and promote products. While it sounds promising, I’m sceptical about its practical utility. For instance, receiving a recommendation from my bank about which shop to visit doesn’t appeal to me personally.

The true potential of AI in payments is more substantial and lies in areas like fraud prevention. With the rise in fraudulent activities, AI’s ability to analyse vast amounts of data swiftly and accurately makes it invaluable. This is particularly relevant for mobile payments backed by debit or credit cards.

Q2: Can you outline the main types of mobile payments and how AI can be applied to them?

There are three primary types of mobile payments:

1. Debit and Credit Card-Backed Mobile Payments: Examples include Samsung Pay and Apple Pay. These have seen significant growth, especially post-pandemic. AI’s primary role here is in fraud detection. Additionally, as these platforms start enabling payments between customers, AI can assist in monitoring for Anti-Money Laundering (AML) activities. The challenge is identifying subtle patterns that don’t spike like typical fraudulent activities, necessitating advanced AI systems to detect long-term trends.
2. Mobile Peer-to-Peer Payments: Initiatives like Kenya’s M-Pesa have revolutionised financial inclusion. These systems don’t require a bank account, relying on mobile wallets instead. AI can analyse transaction histories to identify potential candidates for services like Buy Now Pay Later (BNPL), which would be challenging for humans to assess quickly and accurately.
3. Instant Payments: Introduced by banks and fintech providers, instant payments are rapidly growing. India’s model, for example, simplifies the payment process with a Mobile Money Identifier (MMID). AI can be crucial here in managing liquidity, especially during off-hours when traditional treasury departments might struggle to keep up with the volume and speed of transactions.

Q3: How can AI enhance the transparency and efficiency of payment systems globally?

AI can significantly improve transparency and efficiency, especially as payment systems interoperate more globally. The G20 initiative to harmonise payment rails aims for enhanced transparency across payment corridors. AI can trace and correlate data from multiple systems, providing useful insights to regulatory authorities, law enforcement, and banks. This is crucial as banks strive to find efficient payment corridors based on cost, speed, efficiency, and reliability.

Q4: What are the foundational requirements for AI to be effective in these scenarios?

The cornerstone for effective AI is high-quality data. For AI systems to function optimally, transactional controls must be robust, identifying exceptions and understanding patterns, payment flows, and customer profiles. This data richness allows AI to provide meaningful insights and predictions.

Q5: Do you see generative AI playing a role in these operational areas?

I’m sceptical about the role of generative AI in these operational areas. Operations and execution require transparency, auditability, and compliance, which generative AI currently lacks. These areas demand specialised AI tailored to specific use cases. While generative AI has its strengths, it’s not well-suited for high-volume, low-value transactions that require clear data-driven decision-making.

Q6: How do you foresee the scalability of AI in the context of mobile and instant payments?

Scalability is crucial as mobile and instant payments are low value but high volume, and their growth is expected to continue exponentially. For instance, our white paper with Kapron-Asia highlights that instant payments tripled in volume since 2020 and are projected to rise at a CAGR of 16.7% from 2023 to 2028. Countries like India, Brazil, and regions like Asia Pacific and the Middle East are leading this growth. Participants need technology that can scale accordingly, and AI will be pivotal in managing this growth efficiently.

Q7: What final thoughts do you have on the integration of AI in the payments industry?

AI offers immense opportunities as we move towards an instant payment future. The first step is establishing robust transactional controls to provide high-quality data. This data will fuel AI systems, enabling them to deliver significant benefits. While challenges exist, the potential rewards make AI an essential component of the future payments landscape.

Looking ahead…

The integration of AI in payments holds immense promise. As we move towards an era dominated by instant and mobile payments, the ability to scale efficiently and securely becomes crucial. AI’s role will be pivotal in managing this growth, ensuring that payment systems are robust, transparent, and capable of delivering real-time insights.

While challenges remain, the potential rewards make AI an indispensable component of the future payments landscape. Establishing strong transactional controls and ensuring data integrity will be key to unlocking AI’s full potential, paving the way for a more secure, efficient, and inclusive financial ecosystem.

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Roland Brandli, Strategy Director at SmartStream, brings over two decades of experience to the company. In his current role, he leads the development of strategic product initiatives, leveraging his extensive background to analyse market trends, foster innovative ideas, and cultivate key client relationships. Previously, Roland served as Strategic Product Manager, overseeing the launch of cutting-edge solutions such as AI Reconciliations, Digital Payments, Trade Process, and Advanced Payments Control. Prior to his tenure at SmartStream, Roland held positions in banking back-office and operations departments in France and Switzerland.

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