Receipt capturing with AI: Determine the degree of automation in advance
3. April 2021
„… we can extract 100% of the data correctly from all document types!”, up to this point the webinar presentation on the topic of “Digitalisation in Invoice Reception” was unspectacular, but this statement made me sit up and take notice. I eagerly awaited the challenging questions from the attendees at the concluding Q&A session. But nothing! Nothing at all! This 100% statement on the degree of automation in receipt capturing was apparently accepted. I hereby take this as an opportunity to face the facts and explain the BLU DELTA practice.
But first: What is the “typical market” reality?
When it comes to automated receipt capturing, the automation rates – which refer to the percentage of a company’s receipts that are automatically returned as correct and subsequently posted blindly – cannot be lumped together. The comparison with master data plays a major role here. However, a comparison can only help if the upstream data extraction has been carried out successfully. In addition to the variety of layouts (usually corresponding to the number of suppliers), the recognition rates depend above all on the quality of the invoices (scan, resolution, stamp, handwritten remarks, etc. influence the quality). With the systems commonly available on the market, individual layouts are “trained”. This means that you have to “train” the fields of unknown layouts three to seven times. Thus, 100% is wishful thinking and the actual recognition rate varies greatly depending on the variety of invoices and the “training” effort one is willing to invest. If the variety of layouts is low, the risk and the effort are limited. However, if the variety is high and the volume is large, a close look is required!
Security through evaluation
Of course, it is better if the recognition rate can be determined in advance. With general AI models, the customer can evaluate the quality in advance with their own receipts. Individual invoices can be tested directly via our BLU DELTA system on our website. For a test with several invoices, online or API access can be requested free of charge, or a potential analysis can also be commissioned for sufficiently large quantities of receipts.
The BLU DELTA AI Potential Analysis – a statistically backed prediction
With the potential analysis, the customer receives a detailed report on the expected recognition rate per data field as well as on the overall recognition rate for the receipts circulating in the company within a statistically backed confidence interval.
Together with the customer, we determine a representative sample. Based on this invoice or document sample, the image data is analysed in a basic analysis and the target data is annotated and compared with the output of the BLU DELTA API (benchmark). Based on this, a detailed report on the quality of the documents and a prediction of the recognition rate of our AI model is created. In addition, the report also provides information about the optimisation potential. Thus, the customer has a secure basis to determine the degree of automation in advance.
Custom AI model as a by-product
And it gets even better. The output of the potential analysis – if helpful – is also an AI custom model optimised for the company. This model can be immediately tested live via our API and/or workflow components or directly integrated. Thus, the customer receives what BLU DELTA promises and there are no unpleasant surprises. But this much can be said in advance – it’s not 100%!
BLU DELTA is a product for the automated capture of financial documents. Partners, but also our customers’ finance departments, accounts payable clerks and tax consultants can use BLU DELTA to immediately relieve their employees of the time-consuming and mostly manual entry of documents by using BLU DELTA AI and Cloud.
BLU DELTA is an Artificial Intelligence by Blumatix Intelligence GmbH.
Author: Christian Weiler is a former General Manager of a global IT company based in Seattle/US. Since 2016, Christian Weiler has been increasingly active in various roles in the field of artificial intelligence and has strengthened the management team of Blumatix Intelligence GmbH since 2018.
Contact: c.weiler@blumatix.com/span>
