All kinds of otherwise routine enterprise operations have been rethought and reworked over the past three months, and financial tasks are no different.
Artificial intelligence (AI) and machine learning (ML) are being employed to make some of these shifts more effective, especially for organizations that are newly handling enterprise finances remotely. The companies providing these financial solutions hope that they will continue to prove useful down the road, even if other business operations revert back to their previous state.
For example, even if other operations have changed significantly, companies of all kinds still need to make purchases, whether that is physical items or the services of employees and other companies.
One company, Stampli, uses machine learning to simplify and streamline the work of accounts payable departments to ensure that purchasing happens smoothly, even under current circumstances, said Eyal Feldman, the company’s CEO.
At any organization, accounts payable ensures invoices are paid correctly and on time. “It becomes a very complex collaboration process,” Feldman said — one that requires answers and confirmation from a variety of people along the way.
Ensuring that that process is done both accurately and quickly isn’t necessary only for making sure that expenses are taken care of in a timely manner, though that is important.
“The more accurately you do that, the more accurately you can look at the reports of the organization and look at what’s really going on,” Feldman said of allocating expenses via invoice verification and assignment.
Stampli is designed to help with that process by turning invoices into a communication tool that keeps in mind what people actually like about email, Feldman said. The software employs machine learning to analyze the various components of an invoice and to move their verification, assignment and approval along by communicating with the correct parties at the correct time.
“We took a complex problem, and we simplified it,” Feldman said. Through this communication, the process keeps moving. Everyone who has to touch an invoice has access to it, he said, and users will receive reminders if they have not provided needed information.
That can be especially valuable with more people than ever working remotely. The procurement process has become more difficult because teams are working remotely. “It’s quite a challenge in normal days as well, but when you put people at home, it’s even harder,” Feldman said. “You can’t just chase them in the hallway to get answers.”
Artificial intelligence fuels that simplification, but Feldman realizes that the term’s buzzword status can be a distraction. If it were up to him, he said he’d focus on the automation and remove the word “intelligence” from the conversation.
“The idea here is to really be helpful and give you the information when you need it,” Feldman said. “It’s not about replacing the human factor; it’s about power boosting the human factor.”
Another company, Auditoria, also uses artificial intelligence and automation to ensure accounts payable, accounts receivable and auditing tasks happen quickly and more accurately, said Nick Ezzo, the company’s vice president of marketing.
“Complex tasks like cash flow forecasting are executed in a fraction of the time it takes a human, with a level of accuracy all but impossible to achieve without AI-based algorithms,” Ezzo said of the company’s SmartFlow Skills.
Software automation for enterprise finances aren’t entirely new, Ezzo said. But ML and AI can, it’s hoped, make those solutions smarter and seamless.
“At Auditoria, our mission is to provide a platform that acts as a veneer on top of the ERP [enterprise resource planning] system, managing and executing traditional accounting functions in much the same way a person would,” he said. That work, as with Stampli, involves automated actions such as payment status and approval updates for accounts payable services and cash flow forecasting.
Auditoria can do some of the heavy lifting right now for remote teams by automating data collection and normalization, which gives finance teams more time to act on that data, Ezzo said.
“For example, audit preparation doesn’t need to be performed by teams of people working late into the night in conference rooms,” he said. “Auditoria automatically collects the evidentiary data required for an audit, while a remote finance professional oversees any exceptions and reviews the output.”