Among the elements that make up working capital, there is one that is implicitly more complicated to control than others: Customer receipts. Although all companies should, ideally, be organized to monitor customer invoices and payments, many still do not have the necessary tools for minimum monitoring, and too few are equipped to optimize collection. Excel spreadsheets are still very much in evidence. The teams responsible for collection are frequently not targeted, they use processes that are not very well automated, and which are reactive rather than proactive. In simple terms, the primary objectives of all companies in the area of debt collection are to name customers in arrears and to monitor the history of contacts made with them. However, such practices fail to provide an accurate picture of customer collections. 

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When a company's objective is to improve its cash management and working capital, it becomes imperative to maximize collection efforts and automate as many of the less strategic tasks as possible. This is where Artificial Intelligence (AI) comes in. By analyzing the data available in companies' ERP systems, AI optimizes the efforts of each employee by targeting the customers for whom the cash or risk impact is the most significant for the company. AI also anticipates customer payment problems. This allows the team to take appropriate action before the problems occur. In short, AI helps to automate all the steps that can be automated. This allows teams to focus on tasks that require personalized intervention, allowing proactive actions that alert the team to the risk of non-payment before it occurs. AI will also provide a more accurate view of expected cash receipts, thereby refining cash management. 

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