"The overall perception of AP in 2020 continues to rise. 55% of all businesses now perceive the AP function as "very" or "exceptionally" valuable to organisational operations," according to the Ardent Partners' 2020 Accounts Payable Report.
While the perceptions and expectations of the Accounting function are increasing, Ardent Partners cite basic challenges facing AP teams, including:
Long approval times
Too much paper
Handling supplier inquires
According to the Ardent Partner report, the overall trends for 2020 are to improve insights and give up paper and includes these common themes:
Solve the tactical and manual issues
Create an intelligent component to provide transparency, and therefore visibility to management
Of those surveyed, AP teams’ objectives include:
47% want to eliminate paper and reduce manual tasks
40% want to implement AP automation
48% want to improve AP reporting and analytics
Yet with all the talk about digitisation, AP still struggle with automated data capture (56%).
According to SSON, only 17 percent of invoices received by AP departments in the US arrive via an electronic portal or electronic invoicing network.
How to Become a Best-In-Class AP Team
Ardent Partners compiles a yearly report with benchmarking statistics for “Best-in-Class” organisations, these traits include:
The cost to process a single invoice is just over US $10
The time it takes to process an invoice is about 8 days
The invoice exception rate is around 22.5%
Ardent notes these best-in-class performers use automation technology to transform their invoice processing, resulting in nearly 6x lower than the industry average for invoice processing.
Processing invoices quickly is key, but what if your suppliers don’t provide electronic invoices? Automated data capture (56%), document scanning (69%) represent manual intervention that slows productivity. Many high performing AP teams use capture technology, like Optical Character Recognition (OCR) to handle structured documents. And OCR could work – for some structured documents and only if the format doesn’t change. What happens when you onboard a new supplier and their invoice format doesn’t adhere to your existing template?
Cognitive Machine Reading (CMR) presents the opportunity for straight-through invoice processing. The premise of this technology is simple. Instead of data capture being based on a template, CMR uses fractal technology, along with AI to determine shapes. These shapes are then handled by Machine Learning technology that learns what these shapes are. CMR then classifies this data.
In the case of invoice processing, regardless of format, CMR technology can ingest and digitise all AP data. Is a supplier’s invoice in a pdf or image? Or what if the supplier updates their accounting system and the format of the invoice changes, such as the amount total? Or that the purchase order number is now in a different place on the page? CMR handles all these formats and changes easily. What about semi-structured invoices, as in a pdf or image? Again, the technology behind CMR allows information to be captured and digitised efficiently, based on the fields your AP team needs to process payments. It won’t matter if your invoices are one page or 1,000 pages, CMR will locate, ingest and digitise only the information you need.
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The business benefits are simple: the faster the information is digitised, the faster you can process the invoice. This will not only make your suppliers happier but also allows you to manage cash flow better. With CMR’s confidence scoring, you’ll know right away how accurate your data is and over time the accuracy improves. The exception handling is reduced, now that the data is captured accurately and quickly – the first time. And you’ll be able to take advantage of early payment discounts, which boosts department profitability.
Best of all, CMR provides visibility and transparency to invoice processing, showing you what is working efficiently.
Unfortunately, paper documents and invoices aren’t going away anytime soon. CMR is the solution to handle all your documents and data types, regardless of format. And with the goal to make invoice processing, faster, easier and accurate.
See how Cognitive Machine Reading handles invoice processing.