Article | 6.5.2022

Invoice process automation with RPA and AI


Processing invoices is mandatory yet time and resource consuming task for organizations. Even if the invoice processing is electronic and possibly done by an external partner, efficiency can be improved when software robots fortified with AI help with validation and filling in the gaps. Read on as we discuss how RPA and AI has boosted our customers’ invoice processing.

Invoice processing is a task in financial administration that ties up a lot of educated and valuable human resources. It strains both the financial administration team’s time as well as the business team’s time in approvals and corrections.


Typically the financial administration team has to assign each invoice to the right approver allocate it to the right cost center, tag it for the right category and amend the invoice data with internal accounting information. This storing of invoices is laborious manual work that creates little value. The business team also needs to check and approve the invoice before payment, after which the invoice goes back to finally be processed by the financial team. Depending on the amount of the invoices, this process can demand dozens or even hundreds of hours of work each month.

How does RPA in invoice process automation work?

Many routine and rule-based workflows in accounting can be automated with RPA, including invoice processing. Often pure RPA solution handles well the scenarios that use solely data found on the electronic invoice itself, ideally a computer-generated document, complemented with a business ruleset for processing.


Scenarios with larger amount of invoices and/or differing type of invoices (scanned etc) generate variations to a degree that a pure RPA solution cannot process 100% of the material. We need to think best complementary technology that works together with RPA to recognize various formats of invoice documents.


In addition to recognition and parsing the material, the rule-based RPA may need intelligence such as a suitable machine learning model to predict missing pieces of information that are necessary to correctly process the invoice end-to-end.

AI and machine learning in invoice process automation

While RPA has the “hands” for doing the manual tasks of the invoice process automation, it lacks the brain. Enter AI and machine learning. As described above, processing invoices requires several cognitive decisions: assigning to the right approver, allocating to the right cost center, and so on. These decisions can be tackled with predictive modeling.


For a cost-effective solution there are plenty of ready-made ML models (available as SaaS) for reinforced learning. This means to practically solve the invoice processing task so you don’t need a team of data scientists to develop algorithms. Trick is to understand the problem, collect necessary amount of available data to teach the model and then run tests to determine the best solution. Ideally so that the AI/ML module plays nice with the RPA “hands” so the overall automation fulfills the need without a tech headache.


We implemented this RPA and AI-fortified automation for our customer Posti together with Posti is a finnish logistics giant with hundreds of thousands of customers and thousands of invoices to process each month. Their invoice processing is now automated with a software robot running on UiPath that interacts with Aito’s AI. The robot reads the data in every new invoice and asks Aito to predict the correct values. You can read the whole story here. Posti is digital forerunner and Forbes wrote about the digital transformation journey here.

OCR in invoice processing

We also implemented another intelligent invoice process automation for our customer Kekäle. The organization was already using an external invoice management service, but the manual workload for Kekäle’s financial administration teams was still building up due to growth of their business and a new way of allocating expenses more precisely. They wanted to streamline their invoice processing and the invoice management system didn’t meet their individual needs.


Sisua implemented a software robot that reads the invoices entered in the system and determines where the invoices are directed. Some invoices are sent electronically and some as paper, which are scanned into pdf files. The robot recognizes these pdf files from image to text format by using OCR (Optical Character Recognition) technology. Machine learning was also used in allocating the invoices. You can read the whole story here.

How AI and RPA improve invoice process automation?
  1. Processing invoices is considerably more efficient
  2. Employees’s working time is freed up for more productive tasks
  3. The accuracy of the process is improved and the number of errors is reduced
  4. Policies and data are more consistent
  5. Automation can be built to meet individual needs
  6. The service platform and technology are easily scaled to other processes
  7. Automation improves statistics

In both Posti and Kekäle examples, the intelligent automation boosted the efficiency of their invoice processing significantly. The automation reduced the workload on Posti’s Accounts Paybale team while boosting the speed of invoice review. Likewise for Kekäle, the automation processes most of the invoices, reducing the manual workload by 85 %. Both Posti’s and Kekäle’s teams can now focus on more productive tasks.

“We have developed the service better all the time according to our needs and it is easy to follow the robot's work. Most invoices now go forward automatically and do not require manual processing. This has freed up a lot of working time from monotonous storing of invoices to other more meaningful tasks” states Elisa Huotari, from Kekäle's Financial Administration.

Besides speeding up the invoice processing, the accuracy in the process was improved. Humane errors were reduced, and the robots check for things that might go unnoticed by humans and report if something is wrong. For Kekäle, the robot also patches the deficiencies of their invoice management system. It corrects errors in the system’s interpretation and has created special rules for certain suppliers. This way the automation meets Kekäle’s individual needs better.


Sisua’s service plarform for Kekäle also enables process automation to be seamlessly extended to new automation use cases like order processing or inventory management. Likewise for Posti, their RPA team now has the ability to scale the AI technology for countless other business processes.


All in all, automation boosts efficiency and accuracy while reducing manual workload in several financial administrative processes. Read more about where process automation can be used in financial administration here.

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