Big Data and a Boatload of Data: A Perfect Match
The Need: Cut Costs and Employee Turnover Associated with Accounting Activities
A large company needed to process about 75,000 incoming invoices per year, which required two full-time employees to categorize and evaluate the documents. The tasks were repetitive and time-consuming, leading to high turnover rates among employees. However, humans were still needed to handle invoices that couldn’t be processed by OCR (optical character recognition) software.
The Challenge: Automate the Invoice Classification Process
The company needed to extract the following data from each invoice to categorize and assign it to one of over 100 cost accounts:
- Invoice date
- Payment deadline
- Customer identification number
- Invoice number (a combination of letters, numbers, and characters)
- Invoice amount
- Supplier organization number
- Supplier’s bank account
- Supplier’s name on the invoice
The data was too complex for OCR systems, and the invoice processing module needed to be integrated with the company’s infrastructure.
The Solution: Custom NLP Algorithms
We implemented custom-made classification and normalization machine learning algorithms based on natural language processing (NLP). The model was trained to extract relevant information from invoices and categorize them accurately.
The Result: Invoice Processing Time Reduced by 75%
The custom implementation extracted the whole text from an invoice, with a performance of over 1,000 invoices per hour (about 6 hours to extract the text from 7,047 invoices). The human double-check process was reduced by three-quarters, and the algorithm minimizes human input over time.
Conclusion
By implementing a custom NLP-based solution, the company reduced invoice processing time by 75% and minimized human intervention. This not only reduced costs but also gave the company a significant competitive advantage in its industry.
FAQs
Q: What is the benefit of using machine learning in accounting?
A: Machine learning can automate repetitive tasks, reducing costs and improving efficiency.
Q: How does NLP help in accounting?
A: NLP can extract relevant information from documents and categorize them accurately.
Q: What are the benefits of using a combined ML + rule-based approach?
A: A combined approach can result in higher accuracy and better performance.
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