Genpact's Smart Collect application uses machine learning to predict invoice overdue status by analysing historical collection patterns in a company's Accounts Receivable process. By collecting data on invoice amounts, vendors, and payment terms, the application can accurately predict the invoices which are likely to be delayed in collection. By assigning the risk buckets to open AR the application is helping companies efficiently put focus on their overdue and adapt different collection strategies for the different AR lines based on risk bucket associated.
This is where Genpact and Celonis Combine their Strengths:
Allocates open AR invoice lines to risk buckets (ontime, delayed by 60 days, 120 days, 120+).
identify the open AR predicted amount in these risk buckets against agents, invoice office, and countries.
Review the closed AR (collected amount) against these predicted buckets so that collection strategies can be evaluated and modified as needed.
Classify invoices into high, medium and low risk based on expected time they will take to be closed.The top table shows the sum of invoice amount and their predicted buckets by when those amounts will be collected (120+ days, on time, within 120 days or within 60 days). This view can be filtered by customer, invoicing office, collector and country. The table below shows details for all Open ARs and the prediction for when they will be closed.
Review historical performance of closed invoices and the prediction model. Charts show the distribution of amount paid by various invoicing office and country. The lower left bar chart shows the predicted amount to be collected on time against the stacked graphs showing amount actually collected. Below right bar chart shows the predicted amount to take 120+ days for collection with the stacked graphs showing amount actually collected on different buckets.
Here we see manager-level insights for Closed ARs. We can see the total amount collected under each manager by different agents under them.
This page summarizes the performance of the customer with the highest Open AR. The below graphs show the monthly trend for total collected amount and due amount, total invoices and open invoices, and predicted and collected on-time amount.
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