“FROM THE CONSUMER TO THE COMMERCIAL WORLD” – HOW AI IS DRIVING INTELLIGENT PAYMENTS

by Russell Bennett, chief technology officer, Fraedom

The world of banking and financial services is still seen as one of the more conservative sectors of the economy today but if organisations operating across these marketplaces want to drive competitive edge and business advantage in the future, they can no longer afford to ignore the consumer-driven pull towards the use of artificial intelligence (AI). People are used to these technologies in their everyday lives. They are used to smart software telling them what they want to buy next even before they realise it themselves.

Today, it’s increasingly vital that banks, financial services organisations and financial departments within enterprises are all in touch with these trends. They need to start looking at the benefits that analytics and other predictive technologies can bring them. Their employees and customers will expect them to do so.

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The good news is we are starting to see the use of AI growing in the commercial finance environment now. So far, use cases have mainly been around streamlining operational processes.

Take the introduction of digital expenses platforms and integrated payments tools, both of which have the potential to significantly improve a business’s approach to how it manages cash flow. By having an immediate oversight, through live reporting of all spending from business cards and invoice payments, as well as balances and credit limits across departments and individuals, businesses can foresee potential problems more quickly and react accordingly – and they can go beyond this too. All these services become even more powerful when combined with technologies like machine learning, data analytics and task automation.

We are also seeing growing instances of AI and automation being used to streamline payment processes in banks. Cards can be cancelled, or at least suspended, quickly and easily and without the need to contact the issuing bank, while invoices can also be automated, to streamline business payments. This means businesses can effectively keep hold of money longer and at the same time pay creditors more quickly. Moving beyond straightforward invoice processing, intelligent payments systems can be deployed to maximise this use of company credit lines automatically.

Looking ahead, we see a raft of applications for AI in the payments management field around analysing data with the end objective of spotting anomalies in it. With the short and frequent batches of payments data used within most enterprises today, it is unlikely that even the best trained administrator would be able to spot transactions that were out of the normal pattern. The latest AI technology could be used here to tease out anomalies and pinpoint unusual patterns or trends in spending that could then be investigated and addressed.

They also have the potential to shape the way that payments are made in the future. One of the hottest topics currently under discussion across the commercial payments sector is the thorny issue of integrated intelligent payments. How can enterprises use the latest available artificial intelligence technology to work out the best possible payment option for each individual transaction?

Accounts payable teams will soon need to be able use payments platforms to assess not only how much working capital they have on their corporate cards and what rates they have on their purchasing cards but also what the most sensible choice for payment method would be for each every payment, be it BACs, wire, cheques or even just old-fashioned accounts payable.

Indeed, there is likely to soon be a case for this kind of technology to effectively ‘fit in’, in process terms, between the accounts payable department, and the payment itself, helping the business decide what makes best sense for them as a payment methodology based on the business rules and existing deals that they have in place today.

Future Prospects

We also see a raft of applications for AI in the payments management field around analysing data with the end objective of spotting anomalies in it. With the short and frequent batches of payments data used within most enterprises today, it is unlikely that even the best trained administrator would be able to spot transactions that were out of the normal pattern. The latest AI technology could be used here to tease out anomalies and pinpoint unusual patterns or trends in spending that could then be investigated and addressed.

While this area remains in its infancy within the banking and financial services sector, with technology advancing, financial services organisations and the enterprise customers they deal with will in the future will be well placed to make active use of AI that will help clients track not just what they have been spending historically but also to predict what they are likely to spend in the future.

AI will ultimately enable businesses to move from reactive historical reporting to proactive anticipation of likely future trends. We are entering an exciting new age.

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