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AiVidens

Address

Av. des Volontaires 19, 1160 Auderghem, Belgique

Contact

Edouard Beauvois

Business sectors

Description

AiVidens provides a Predictive Risk Management solution (PRIM) that can be applied to any Debt Portfolio. Thanks to specific algorithms and to AI, PRIM assesses whether a customer will pay and when. PRIM therefore allows companies to anticipate payment issues and segment Debt Portfolio according to dedicated payment profiles & risk types.

Products & Services

Cash is key for every company. However, in many cases collection processes start very late, increasing the risk of never getting the money back. This is a pity, because data exist which could then be used in order to anticipate payment issues early enough in the overall cash process. Thanks to specific algorithms we created and thanks to Ai, our solution helps companies make a better use of their data in order to predict whether a customer will pay and when. It also calculates more than 20 risk indicators designed to help both the management and the operational teams to set the right priorities for the right financial strategy. Therefore, instead of starting the collection process once invoices are overdue, with our solution, companies can now, as early as the order, or a few months before the due date, understand whether payment issues will occur, and act accordingly. With our solution, companies will benefit from a clear view of how their debt portfolio is structured, an alert system letting them know when a customer or an invoice is at risk, and predictive cash management data. They have now all the tools and data to reduce their bad debts, improve their cash collection processes, chose the right lever and to optimize their cash management.

Innovative Aspects & Advantages

Use Artificial Intelligence to determine whether a payment will be made and when. Apply specific algorithm to assess the risk related to the debt portfolio. Start working with Predictive Risk Management. Turn traditional collection processes into dynamic collection processes with predictive data.

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