At a time when three-quarters of businesses say they plan to invest in accounts receivable (AR) automation, predictive analytics has come to the fore.
Predictive analytics offer some of the most promising returns on investment. The solutions leverage artificial intelligence (AI), machine learning (ML), data mining, statistics and a host of other technologies to analyze current vendor data to help financial teams make informed decisions, as reported in the “Working Capital Playbook,” a PYMNTS and YayPay collaboration
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These systems can project which customers have the highest likelihood of being late, for example, giving AR team members the heads up about when they need to take a hands-on approach.
Deploying Automated Solutions
Automating back-office functions was once the purview of larger firms, but more recently, it has been filtering down to smaller companies, YayPay CEO Anthony Venus told PYMNTS in an interview.
Read more: Experts Say Supply Chain Challenges Spur New Digital Payments Innovations
It couldn’t come at a better time. The current state of the economic world can be described as precarious at best, and AR inefficiencies can potentially hurt the entire business. Organizations need all the help they can get to ensure smooth working capital — and a greater chance of success.
For example, late payments are endemic in the AR space, and they can have dramatic ripple effects in terms of vendor loyalty and companies’ financial well-being. Businesses that have deployed automated solutions such as predictive analytics have improved efficiency dramatically.
Putting a Dent in Delayed Payments
One key metric when measuring AR effectiveness is days sales outstanding (DSO). A shorter term generally leads to a more reliable cash flow. Eighty-eight percent of companies that harness AR automation report shorter DSO cycles. This contrasts with businesses that don’t use AR automation, which saw DSO increases of up to 20% during the previous year.
YayPay’s predictive analytics system, for example, was found to improve productivity among AR teams by a factor of three, lowering DSO cycles and freeing up funds tied up in AR.
Automation and predictive analytics can help AR teams put a significant dent in delayed payments, missing invoices and other expensive and time-consuming obstacles. The time and money these processes and technologies save can be put toward spotting and fixing other AR challenges, which could result in a more productive, positive experience for AR staff and vendors alike.