B2B Payments

Artificial Intelligence Lands AR In Uncharted Territory

Artificial intelligence (AI) is finding success in the back office, and that includes in financial systems and accounting departments. AI and machine learning have the potential to automate tasks that would have otherwise taken up valuable time of financial professionals and to provide deeper insights from Big Data that human power could not reasonably have achieved.

But AI is introducing uncharted territory for the back office too. One of the most dramatic ways is in the area of compliance and liability: If a machine makes the wrong call, who’s to blame?

Financial executives aren’t ignoring this trend either. Research released last month from BlackLine found nearly half (46 percent) of finance professionals are already using AI in the workplace, and most say accounts receivable (AR) and accounts payable (AP) will see the largest disruptions from the technology.

There is less consensus when it comes to the issue of liability, however; BlackLine’s survey found just 16 percent of professionals believe liability should fall on the developer of AI tools, while 45 percent instead said it should fall on the shoulders of finance executives.

Analysts recommended that companies tread carefully in this regard. But in some instances, the benefits of AI may outweigh the risks, especially in areas like accounts receivable, and especially when the technology can address the long-lasting frustration of late invoice payments.

Pay360, a U.K. payment service provider with a strong presence in the public sector, recently announced a partnership with collectAI to deploy artificial intelligence in corporates’ AR departments. The solution, the companies said earlier this month, can be particularly helpful in addressing the nation’s late payments challenges; data from Bacs released last year found that late invoice payments cost U.K. companies billions of dollars every year.

Stephen Ferry, managing director, and Andrew Davies, product director, at Pay360 explained to PYMNTS in a recent interview that the deployment of AI in certain aspects of AR isn’t going to raise concerns over liability. Take, for instance, the issue of customer engagement: It’s key to providing a good customer experience and to making sure clients pay their invoices as quickly and conveniently as possible.

The executives noted that AI can be quite impactful in boosting payment collection rates.

“Some challenges we have found for our customers over the last 18 months have been around faster payments and late payments,” said Ferry. “Our customers want to make sure their customers use the most appropriate, fastest method to enable payments to take place.”

To achieve this, companies have to take into account the device through which customers pay, their preferred payment rail, even details like what time of day is best to contact them about a payment that’s due.

“This is something our customers can be very keen to wrap their heads around,” added Davies, “but it can be daunting.” He noted that consumers may find a vast array of communication and payment platforms — from social media to smartphones — a benefit, but often, companies find these choices can be quickly overwhelming.

But the customer payment and engagement experience is “critical,” said Davies, and if clients are going to pay their invoices faster, this experience has to be optimal.

“If you make it an interaction the way the customer wants to interact, they are more likely to hit the button and pay,” Davies explained. “It means they send money on time, and the whole ecosystem flows much better. If you create barriers, you may lose money just through confusion.”

Artificial intelligence can aggregate the data necessary to pinpoint how that experience should happen and learn over time the best way to engage with clients for the best chance of receiving payment as soon as possible.

“By using artificial intelligence and machine learning, we end up having an ability to understand the customer,” said Ferry. “As you get more interaction with the customer, you end up working out what the right method of communication is, what the right time for communication is, and understanding what mode of payment the customer prefers. That’s all going to increase the propensity to recover money a lot faster.”

None of this raises issues of liability, the executive added, because tools like these are simply using existing data to enhance customer engagement. But there are certainly areas of accounts receivable and corporate finance in general that begin to walk the liability line when AI is involved.

Davies pointed to solutions Pay360 offers that include customer risk analysis as one example.

“We’ve got other work streams in this area, where we’re doing risk-based decision-making,” he said, “to decide what a good and bad customer looks like, or a potentially risky customer that you want ... to trade with.”

Chatbots are another area the executives said will be disrupted by AI, as companies look to achieve this enhanced customer engagement and customer experience; indeed, several other corporate finance companies have already deployed AI-powered chatbots to facilitate processes in the corporate accounting space.

This is also another area that could present uncertainty over the legality of having a machine make decisions for a company.

“Another key thing for receivables is communicating with the customer in the right way, and here we’re getting into the chatbot range of things,” said Ferry. “Now, solutions like Alexa are starting to overlap this landscape of the contact center, and it raises legal questions.”

“I think this has the potential to have its own legal ecosystem,” Davies noted.

While the legal side of AI in corporate finance and other back-office functions evolves, there are a few safer bets in which the technology could enhance the AR and payment experience, which has broader implications for the U.K.’s late payments fight — a pressing issue in other markets as well.

At the heart of this disruption, though, is the end payer.

“It’s fundamental that you understand what customer requirements are,” said Ferry. “As a responsible company, it’s important to listen very carefully and understand what their challenges are.”



The How We Shop Report, a PYMNTS collaboration with PayPal, aims to understand how consumers of all ages and incomes are shifting to shopping and paying online in the midst of the COVID-19 pandemic. Our research builds on a series of studies conducted since March, surveying more than 16,000 consumers on how their shopping habits and payments preferences are changing as the crisis continues. This report focuses on our latest survey of 2,163 respondents and examines how their increased appetite for online commerce and digital touchless methods, such as QR codes, contactless cards and digital wallets, is poised to shape the post-pandemic economy.