Digitalizing logistics payments could banish pain-points and reveal new revenues

We are living through a global supply chain reset. First, Covid-19 and a volley of geopolitical shocks prompted businesses to reroute their operations for greater resilience. Now, economic pressures have put supply chains under scrutiny once more. Price rises across energy, materials and logistics are driving companies to make cuts and increase efficiency in their internal teams and external supplier networks. Meanwhile, higher interest rates means that businesses have to carefully steward every dollar of working capital or risk missing out on attractive returns.

The logistics sector is looking at a number of strategies to meet these requirements. A crucial one is arguably the most obvious: modernizing the payments process. Traditionally, supply chains have been beset with inefficient, labor-intensive practices. For example, many freight companies in the U.S. still have largely manual workflows. They send paper invoices and get paid via check. This process can be frustratingly slow, with payments taking days or weeks to arrive. Even worse, it exposes companies to a higher risk of fraud, and traps their data which hinders cost-effective decision-making. 

An even more serious challenge is reconciliation. “About 20 percent of the time there's a discrepancy, meaning the invoice amount or other details don’t match what was expected in the contract. It can sometimes take up to 60 days to solve the issue because companies aren’t empowered with high-quality data to understand the root-cause,” says Matt McKinney, co-founder and CEO of Loop, a logistics-AI audit and pay solution built for shippers and logistics service providers.  

The supply chain is a network of networks and each point of payment friction at every phase adds cost. Ultimately, someone has to pay for the capital that's locked up—they may need to take an expensive bridging loan to make up the shortfall. 

 “The supply chain runs on data. Friction in the payments is fundamentally a data problem: purchase orders don’t match invoices. This is a bad problem for people to solve but a great problem for AI,” continues McKinney. One strand of innovation is using AI to extract and centralize all supply chain and spend data that is trapped in physical documents and manual workflows. With accurate, centralized data, both sides can easily correct invoice errors and have an understanding of why the issue occurred. 

This is something Loop facilitates, and it also allows payments to be made quickly and simply via the optimal method, be it ACH, wire or real-time payments. This is more significant than it might seem. Large companies can have hundreds of people devoted just to processing checks and solving reconciliation issues. These resources could be better deployed elsewhere.