A Look at Intelligent Document Processing and E-Invoicing

Why should a company (or its managers) embrace this shift? The rationale is clear: to conserve resources (e.g., reducing paper usage) and streamline workflow efficiency (e.g., eliminating manual data entry).

Furthermore, staying abreast of developments in this sector is crucial for companies engaged in public sector contracts. Within the European Union, there has been a longstanding push (EU Directive 2014/15/EU) to standardize invoicing and enhance machine readability. This initiative aims to facilitate the automated processing of business invoices. Similarly, in Germany, there is a noticeable shift underway in the public sector towards digital capture and automated processing, away from traditional paper-based document handling.

As a consequence of this transition, legislative bodies in Germany, for instance, have mandated that by approximately 2025, only business invoices meeting specific machine-readable formats may be digitally submitted. Consequently, the pressure on companies involved in public sector contracts is set to intensify in the coming years, marking the gradual escalation of e-invoicing into a pivotal phase.

Returning to the focal point, the intelligent processing of business invoices is paramount within the end-to-end invoice processing workflow, constituting perhaps the most critical aspect of the procedure. For instance, erroneous recognition of the IBAN (International Bank Account Number) could lead to inadvertent payment to the wrong supplier, thereby incurring substantial subsequent costs for the company.

Exploring Two Approaches for Data Field Identification in Business Invoices: AI Integration and Standardized Formats

The ensuing section will delineate two prospective methodologies for identifying data fields from business invoices.

In the initial scenario, data recognition is facilitated through the utilization of artificial intelligence (AI). Presently, various providers—such as Microsoft (utilizing the LayoutLM Model), ABBYY, SAP, and EagleDoc—offer comprehensive solutions for data extraction employing AI technologies. For instance, SAP employs a document reader to parse the extracted invoice documents, thereby discerning and categorizing the pertinent data. AI-driven OCR (Optical Character Recognition) software adeptly identifies and captures invoice data, cross-referencing it with vendor master records. Leveraging pre-existing master data, the invoice can be swiftly allocated to the appropriate supplier and designated employee. Furthermore, the classification software proficiently interprets invoice line items and associated values, facilitating immediate alignment with corresponding order data. Nevertheless, a commonality across all providers is the iterative nature of invoice processing—a perpetual refinement process. 

public class ZUGFeRDReader {

    public static void main(String[] args) {
         
        ZUGFeRDImporter zi = new ZUGFeRDImporter("./MustangGnuaccountingBeispielRE-20201121_508.pdf");
   
        //"ZUGFeRD" validation
        if (zi.canParse()) {   
            System.out.println("Total Amount: " + zi.getAmount());
            System.out.println("BIC: " + zi.getBIC());
            System.out.println("IBAN: " + zi.getIBAN());
            System.out.println("Holder Name: " + zi.getHolder());
            System.out.println("Invoice Number: " + zi.getForeignReference());
            System.out.println("Invoice Date: " + zi.getInvoiceDate());
            System.out.println("Invoice Due Date: " + zi.getDueDate());
            System.out.println("Currency: " + zi.getCurrency());
            System.out.println("Tax ID: " + zi.getTaxID());
            System.out.println("Customer Reference: " + zi.getCustomerReference());
       
        } else {
            System.out.println("Invoice is not in the ZUGFeRD format");
        }
    }
}