Can you imagine a more arcane and boring topic than accounts receivable? Unless you are the CFO, controller, chief accounting officer or treasurer of an organization, maybe not.
Anecdotally, as it’s part of the trend to the digital transformation of all things in the department, there appears to be greater interest in this area of the Office of Finance. With populations locked down and the accounting staff unable to work in an office, the need to operate virtually has accelerated the application of technology to finance and accounting departments, which has been long overdue.
The recent focus on technology is welcome news. Our Office of Finance benchmark research conducted before the pandemic revealed that 49% of organizations were at the lowest level of competence in using technology. The research also confirmed our assertion that competence in the use of information technology is essential to achieving better performance.
For example, 88% of organizations that scored at the highest level of competence in using technology perform accounting very well compared to 44% at lowest level. Similarly, 69% of at the highest level perform budgeting and fiscal control very well versus just 18% at the lowest.
Technology is central to the efficiency and smooth functioning of Finance and Accounting. It is therefore essential that the department has a high degree of competence with technology. Needing to deal with a radically different working environment has focused finance department executives’ attention on using technology with a newly felt urgency. They appear to be embracing “digital transformation” to a significantly higher degree than before.
For me, that term just means making full use of proven, practical, and affordable information technology to improve departmental performance, substantially reducing the need for people to do low-value work that computers can do faster and more accurately while achieving better business results. This is especially true for managing accounts receivable.
Managing receivables well is necessary to handle working capital efficiently and to minimize credit losses from customers. It has been a CFO priority for just about forever.
The key metric is “days sales outstanding” or DSO, which measures the average number of days that it takes an organization to collect payment after a sale has been made. DSO is a straightforward calculation, and an organization’s performance is measured against similar types of businesses in similar regions.
It is used internally and externally by bankers, creditors, and equity investors. When performance lags the benchmark, attention to accelerating the collections process is at the top of the list of interventions. Dig deeper and there’s more to managing receivables than keeping on top of late-paying customers.
Organizations must accurately apply incoming payments to the correct customer account and invoice. The process involves taking the customer name or invoice number, finding the associated payment, usually by looking at the associated payment advice or notation on a check, and posting that payment to the accounts receivable invoice in the organization’s financial management/ERP system.
Two equally important objectives in managing the matching process are maximizing efficiency and substantially reducing the latency between the receipt of a payment and applying that to a specific customer and invoice. Matching incoming payments to invoices may seem simple, but the devil is in dealing with the myriad details of processing and accounting for cash receipts and receivables to accurately match the two.
One challenge is efficiently handling volumes of transactions. An organization may issue hundreds, thousands, or tens of thousands of invoices every month, and each of these may have multiple line items that must be reconciled with a payment. Computers, especially those equipped with artificial intelligence (AI) using machine learning, can match receipts with invoices faster than humans and post journal entries to the ERP system.
However, this matching process isn’t always straightforward. It gets complicated when the data accompanying the payment is incomplete or doesn’t exactly match what’s on the invoice. That latter can occur if, for example, the name on the payment advice is different from the invoice because it’s from the customer’s parent organization account.
On the receivables side, complications occur if there are differences between what’s on the invoice and the payment received from the customer. Partial payment differences may be caused by a failure to deliver everything on the invoice, a discount claimed by the customer, a dispute over what was delivered, or a simple mistake.
In some cases, the procedure is further complicated if individual items on the invoice must be allocated back to different business units or legal entities. Using AI means that over time, the system can learn how to accurately make less obvious connections between receipts and invoices and increase its first pass accuracy, improving efficiency, and reducing the need for humans to be involved.
Another source of complexity is the fragmentation of how customers pay. In the old days, organizations sent checks that were accompanied by a copy of the invoice and referenced invoice numbers on the front. Today, money is collected by different banks through multiple methods such as credit cards, an automated clearing house (ACH) direct payment, and, yes, checks.
Payments are sent through multiple channels such as mail, web portals, and email. Organizations can deal with this complexity by using digital methods to retrieve remittances and collect their related information including the invoice number, and put these in a centralized data store. Reducing latency is important because it frees up cash that can then be used in the business, reducing the need for borrowing, and enabling the finance organization to monitor cash flow accurately.
Customer service also benefits, because this affects the timeliness of the customer’s outstanding credit balance, potentially preventing issues arising when a sale to that customer cannot go through because the organization’s system inaccurately shows they’ve exceeded their credit limit.
Historically, an organization’s ability to minimize latency has been constrained by the cost and availability of staff to do the processing. Manually matching a specific payment received to a specific invoice is time consuming and tedious.
Before software was available to manage accounts receivable, organizations dealt with the issue by throwing bodies at the processing problems, sometimes dealing with the cost by offshoring processing to lower-wage countries. Technology has emerged in recent years to improve receivables management, but it’s taken the pandemic to raise awareness of the value of digitally transforming accounts receivable management.
Join us for this webinar on March 25 to modernize your cash application with intelligent automation and reduce unapplied cash by up to 99%.