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