Classification accuracy
Documents in 2 minutes processing speed
A leading federal national mortgage association receives over one million paper documents a year, including invoices, tax statements, and checks from their customers and vendors that must be manually sorted and organized; posing a risk for fraud that could go undetected due to the large volume and scale of these documents.
They wanted to organize their service reimbursement process by automating the digitization of documents and efficiently detecting fraudulent requests.
Google Cloud Vision API
Quantiphi developed a machine learning-based custom document classification model to organize and extract information from these documents into a structured dataset at scale.
