Introduction
In this case study, we will explore how the implementation of our INVOICE Reader Module helped a real estate capital group streamline their invoice processing and data extraction tasks. By leveraging advanced machine learning algorithms, the client was able to automate the extraction of key accounting data from incoming invoices, reducing manual work and optimizing their overall accounting processes.
Client Profile
The client is a prominent capital group that manages real estate properties in Poland and Western Europe. With a high volume of incoming invoices and accounting notes, the client faced challenges in efficiently processing and extracting relevant accounting data from these documents. They sought a solution that would automate this process, improve data accuracy, and integrate seamlessly with their existing Enterprise Document Management (EDM) system.
Challenge
The client’s main secretariat employees were burdened with the manual processing of incoming invoices, leading to inefficiencies and increased workload. They required an advanced solution that could automatically extract key accounting data from invoice documents and seamlessly transfer it to their EDM system. The challenge was to implement efficient algorithms that could adapt to different invoice patterns and extract specific accounting fields accurately.
Solution
Our solution, the INVOICE Reader Module, addressed the client’s challenges by leveraging machine learning algorithms to automate the extraction of accounting data from scanned invoice images. The project consisted of two key stages:
- Algorithm Development and Testing: We conducted an in-depth analysis of the invoice documents, their structure, data patterns, and image quality. Based on this analysis, we developed and tested optimal algorithms that could autonomously extract the desired accounting data fields, such as document dates, sales dates, payment dates, vendor names, net and gross amounts, VAT rates, currency types, bank account numbers, and more.
- Integration with EDM System: We modified the client’s existing EDM system to enable automatic population of accounting data extracted by the INVOICE Reader Module. This integration ensured seamless data transfer and eliminated the need for manual data entry, improving efficiency and reducing errors.
Key Features and Benefits
- Increased Efficiency: The automated extraction of accounting data significantly reduced manual work for the client’s secretariat employees, allowing them to focus on more value-added tasks.
- Improved Accuracy: By leveraging machine learning algorithms, the solution achieved high accuracy in extracting key accounting fields, minimizing errors and improving data quality.
- Time and Cost Savings: The automation of invoice data extraction reduced processing time, enabling faster invoice handling and improving overall operational efficiency. This translated into cost savings for the client.
- Seamless Integration: The INVOICE Reader Module seamlessly integrated with the client’s existing EDM system, ensuring a smooth workflow and eliminating the need for manual data entry.
Results
The effectiveness of our solution was validated through two-month testing periods in the client’s production environment, under the expert supervision of designated client employees. The INVOICE Reader Module exceeded the client’s expectations, achieving a stable accuracy rate of over 85% for all processed documents and extracted accounting fields.
Conclusion
By implementing our INVOICE Reader Module, the client successfully streamlined their invoice processing and data extraction processes. The automation of these tasks not only improved efficiency but also enhanced data accuracy, resulting in more reliable accounting records and streamlined operations. With our solution, the client experienced time and cost savings while freeing up their employees to focus on higher-value activities.
Our tailored solution and collaboration with the client’s team enabled them to overcome their invoice data extraction challenges and optimize their accounting processes. By leveraging advanced machine learning algorithms, the client achieved enhanced productivity and accuracy, positioning themselves for continued success in the real estate industry.