Duplicate bill payments often go unnoticed by creditors. They are usually due to poor data entry which leads to significant losses if undetected. It's all a thing of the past as our algorithm is designed to detect these duplicates. The detection algorithm goes through several stages. First, pre-processing steps are applied to clean up all invoice data. You can think of replacing an "i" for a "1" within an invoice number to solve possible scanning errors.
Then fuzzy string matching is applied to all invoices (records) using the available data attributes in the dataset. Potential duplicate invoices are identified based on a match score shown as a percentage with 100% indicating a perfect match.
Our dual payment algorithm provides the following benefits to your business:
We only use invoice data for this analysis. Using our algorithm, some of the value adding features for detecting duplicate invoices are supplier name, invoice number, amount, currency, invoice date etc. You will receive a specification of the dataset for this.
The resulting matches (incl. match scores) are made available in an Excel file.
In most cases, duplicate invoices do not match exactly. Therefore, we introduced fuzzy matching in our model to identify possible duplicates based on a match percentage.
Billing data is cleaned to find duplicates effectively. Our algorithm cleans up the data and then checks all invoices for duplicates. You will immediately receive an overview of the invoices that may have been paid twice.