Eliminating the pain of invoice processing with Intelligent Process Automation

A study completed by Aberdeen Group found that on average it can take an organisation up to 20 days to fully process an invoice; from scanning, data extraction, validation, to payment queries, essential business checks and payment authorisation. All these tasks are often manually completed by the finance team each day and are vital to ensuring that payments are made on time and supplier relationships are maintained. Invoice processing, therefore, carries a high level of responsibility, but the repetitive nature of the process means that it is time-consuming and sometimes error-prone. It is no wonder then that 50% of industry accounting personnel say their primary concern is eliminating these manual tasks.  

Intelligent Process Automation (IPA) is the ideal solution to address the concerns of finance and accounting personnel, as it enables organisations to reduce the manual elements of invoice processing through automation; improving processing times, minimising errors, but most importantly freeing up staff to complete more rewarding tasks such as conflict resolution and relationship building.

IPA constitutes a wide variety of technology applications (for further information on IPA and other technologies, a glossary of terms can be found here), which can be used alone or in combination to automate certain tasks or end-to-end business processes. It is important for organisations to understand their individual use case and associated business case in order to identify which technologies will deliver the highest return on investment and therefore success.

Invoice Automation

Due to the repetitive nature of some of the tasks involved with invoice processing, many organisations choose to deploy RPA bots embedded with OCR. Bots can be effectively deployed to automate tasks such as data preparation, extraction and entry into finance systems. The rules-based programming of RPA means that it is very well suited for processing invoices which are similar in structure, enabling organisations to automate the handling of their most commonly received documents and is particularly effective at lower volumes where minimal reprogramming is required.

Human in the Loop

For larger organisations, particularly at an enterprise level, where 100,000s of different supplier invoices are received on a daily basis, it may be more effective to deploy a Machine Learning (ML) solution. This technology enables the automated processing of a much wider and unpredictable variety of invoice structures because of its ability to learn. For example, Celaton’s inSTREAM™ Intelligent Document Processing (IDP) platform uses AI and ML to cope with variances in invoice formats. inSTREAM learns through the natural consequence of processing documents along with ‘Human in the Loop’ where the platform collaborates with AP Clerks to enhance its learning. inSTREAM learns from every transaction it processes, therefore as the volume of documents increases, its confidence and accuracy improve to a point where Straight Through Processing (STP) is achieved. In addition, immediate scale and growth are enabled due to inSTREAM’s ability to continually learn without the need for additional programming.

Both technology applications enable organisations to gain significant benefits, including productivity increases, payment discounts and visibility of data, however only through first understanding their business case and identifying the most appropriate technology, can organisations really unlock the full potential of those benefits.


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