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How machine learning is changing the payments landscape

Paul Christensen, CEO of Previse, discusses how the B2B payments sector can leverage AI to implement genuine change

If 2020 was the year the world moved from paying lip service to digitisation to relying on it, then 2021 is the year we leverage technology to implement strategic and sustainable change, writes Paul Christensen

Conversations about how machine learning is going to change our lives have been focused on futuristic, front-end products like autonomous cars. But, machine learning is already transforming legacy business processes that dictate the way businesses operate and determine how economies function.

Earlier this year, the UK Government confirmed £800 million in funding for its ‘blue-skies’ Advanced Research and Invention Agency, which will fund research into uses of Artificial Intelligence (AI) and data. Machine learning clearly has immense potential to solve long-standing issues in how we store, process and harness data. One such use case for machine learning is the business-to-business (B2B) payments market.

Creating simultaneous value exchange in B2B, just like B2C

As of 2019, the global B2B payment market was worth $125trn. Yet, despite recent technological advances, B2B payment still falls way behind its consumer counterpart (B2C) in terms of customer experience and efficiency.

If you go out to a cafe and buy a coffee, you tap the machine with your card, pay £3 and you’ve got your coffee. Imagine, if instead, you said, “Hey, thanks for my coffee. Send me an invoice, I’ll pay you in 60 days.” That would be absurd, and yet, that is how business works.  

Machine learning makes it possible for all corporates to give their suppliers the option of day one payment. But, technology can only go so far. Government and corporates need to do more to bring about a cultural shift in B2B commerce, where prompt payment matches that of the B2C world. Regulatory measures, like the Prompt Payment Code, can only go so far to effect this change. Technology is the key to unlocking a new era of equitable and sustainable B2B payments. 

Building supply chain resilience

In 2019, late invoice payments in the UK amounted to over £23.4bn– this figure has increased since the pandemic. Machine learning enables corporates to identify and flag the very few problematic invoices, so that the rest can be paid immediately. This technology allows suppliers to be paid instantly while large corporates pay on their normal terms. Suppliers unlock much-needed liquidity, while large corporates strengthen their supplier relationships at minimal cost. 

Adopting technology-driven payment solutions enables suppliers to build steady cash flow and create resilient supply chains, without impacting the bottom line of the corporate buyer. Integrating machine learning across the B2B payments landscape also has a global impact as it accelerates the velocity of global monetary flows. Speeding up the flow of money strengthens trade networks, boosts economic growth, and adds real value to the payments market.

Giving suppliers the option of day one payment is just one instance of how the B2B payments industry is leveraging AI and data to implement genuine change. By transforming the legacy business processes that we take for granted – such as B2B invoice payments – machine learning is quietly making the payments landscape a more efficient and agile industry.

Paul Christensen is CEO of  Previse,

Paul Christensen, Previse

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