Predicting Late Payments and Automating Proactive Actions
The Problem: Currently Accounts Receivable (AR) treats every receivable the same is largely reactive. It does not proactively address individual cases which are high risk.
Our Proposed Solution: Predictive analytics using Machine Learning can predict potential late payments or defaults based on analysis of historical data and take proactive measures to correct the problem. Machine learning can also reveal patterns based on years of data and suggest insights to handle payments more efficiently.
ROI: More efficient collections saving several days of AR effort and reducing requirement for manual processing.
AI based Document Digitization and Processing
The Problem: Billing for medical service and collecting payments requires
pulling together documents from disparate sources and requires a lot of
Our Proposed Solution: OCR and AI based document digitization can
help in pulling together and processing all the required documentation from disparate sources to speed up payment processing.
ROI: Reduced DSO which improves bottomline. Reduced manual
processing which reduces costs.
Automating AP and maximizing Discounts
The Problem: Most companies process their invoices as per the net payable terms, however it requires human intervention to tie the invoices back to the MSA document and schedule the payments to maximize the discounting terms for volume and speed of payments.
Our Proposed Solution: OCR and AI based document digitization can help in pulling together and processing all the required documentation from disparate sources and then automatically schedule payments to maximize the discounting terms.