“Real-time payments processing is becoming a reality in B2B,” said Corcentric chief product and technology officer Manish Jaiswal.
Yet, speedier payments will force companies to address accounts receivable and payables inefficiencies.
He stated most organizations, regardless of industry, have problems processing payments due to data quality or transaction execution.
He stated that fraud is always a problem, particularly when data breaches and social engineering schemes get more complex and trick staff into giving money to fraudsters.
“People can be the most vulnerable link in the ‘security chain’ of payment processing,” Jaiswal remarked. Payments’ most vital function—verifying the payer’s identity—is getting more difficult.
AI can improve operations and anti-fraud efforts for merchants and financial institutions. AI and machine learning can examine big data sets in real time to help organizations securely execute or cancel payments.
As Jaiswal said, “there are several areas where AI can and will help make real-time processing a reality.”
As an example of how advanced technologies can improve back-office functions, Jaiswal pointed to accounts payable (AP) tasks and said that many companies still “prominently use” manual processes.
Enhancing Back-End Flows
“There are still a majority of companies that get paper invoices” from suppliers and vendors, he said. Businesses receiving paper bills usually have a third-party supplier or in-house workers enter in the information, which may lead to human error. AI can now assess paper-based or scanned bills, compare them to “master data” on suppliers, price, and other parameters, and “push” approval into the system to speed up payments.
“On the back end, if you improve these processes, this improves your cycle time, end to end,” he told. “Your payment execution could be flawless if you do all this work the right way.”
AI can enhance cash flow estimates for AR. For weeks and months, companies might have millions of dollars in receivables.
“With the help of AI, you can analyze the behavior of a given [B2B] customer and predict cash flow,” he said, and even the invoices and payments that may ultimately be disputed.
Jaiswal said real-time processing has advantages beyond B2B payments. Banks may speed up underwriting and lend to corporate and consumer clients as they compete with FinTechs.
He claimed big data and machine learning are changing whole industries, including retail.
“We’re seeing a transformation where retailers are bringing all the data together across supply chain management and inventory management and point-of-sale systems,” he said.
Optimizing inventory movement and reducing stock-outs is having a favorable impact. Businesses may even use weather data to predict supply chain disruptions. Improve “reverse logistics” by using transaction histories and end-user consumer habits to predict returns.
“This drives efficiencies across the board,” Jaiswal said, “and we’ll see AI become very prominent in the years ahead.”
