How AI can enable instant payments

The world is awash with news and articles on artificial intelligence (AI), and the payment industry is no exception. Recently we have learned that Mastercard have rolled out an AI tool to spot real-time payment scams, U.S Bank is using AI in business travel management, and conferences are filled with talks on an AI future.

What’s needed, as always, is a nuanced view of the phenomena of AI in banking that takes into account its potential while dismissing the ‘hype’. It is particularly germane to one of the longest problems in payments: the sometimes considerable delays between payments.

AI in Payments

In payments, ML has similar applications. Research shows that 55% of businesses are still owed invoices from 2022 in May of 2023. There are a lot of reasons for this, not least among them the rising cost of living and electricity prices, but the sheer amount of red tape around payments is a major issue.

B2B payments in the UK are the fastest in Europe and are getting faster, but still average 23 days from invoice to payment. Compare this to B2C payments, where money is typically transferred instantly from account to account or customer to business. Instant B2B payments are the holy grail, but it isn’t always an option for legal and compliance reasons – AI can identify when it is an option and therefore when instant payment can be offered.

The starting point of any payment has to be in making sure that the person paying or being paid is who they say they are through KYC and AML checks. This whole process is a time-consuming, torturous workload because of the sheer volume of documents to examine. Fortunately, AI and ML tools don’t mind sifting through reams of paper or digitally scanned documentation. With natural language processing, AI and ML can speed-read documents, verify whether they’re fake or genuine, and cross-reference them with other sources to ascertain authenticity.

In the case of more complex payments, AI can identify shortcuts and efficiency savings or automate the more mundane tasks. AI’s ability to process massive datasets and compare a multitude of variables in real time is a game-changer. It can facilitate straight-through processing of payments, with far more accurate decisioning, and smart routing and distribution of payment transactions to improve authorisation and settlement. For example, AI can help a payment provider decide whether a specific transaction needs to go through two-factor authentication.

AI-powered payment reconciliation can automatically match incoming payments with outstanding invoices, reducing the need for human intervention and speed up reconciliation times. This will hopefully lead to some of the £50 billion or more in late payments owed to UK businesses being reduced.

What’s next for AI in payments?

You will notice by now that we are talking about AI systems in payments and finance in the present tense. This is because they have been present in the larger finance industry for years – decades in some cases. When AI is being mentioned today, it is usually in reference to new innovations in the field, namely large language models (usually referred to as ChatGPT, though this is one of many companies working in the field.)

Despite all of the talk about LLMs and payments, it is difficult to see what these systems offer that isn’t already available through ML. Needing to produce large bodies of convincing (but not entirely convincing) text isn’t one of the pain-points of the payment industry compared to payment facilitation, cross-border payments and fraud. It might be the case that these technologies will lead to advances in ML that can make existing systems better able to parse the massive data sets generated by a payments company during its day-to-day activity.

As always, the payments industry needs to have a realistic view of both the technology behind AI and what will really move the needle for them. Making the majority of payments, whether from consumers or between businesses, instant, especially across borders, would go a long way to fixing one of the payment industry’s most persistent problems. The specific pain points that need addressing in payments are varied and always evolving, but we are already seeing how AI can improve outcomes for payments companies.

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