Payment trend forecasting

Need

Managing customers who do not meet payment deadlines is a common issue for companies in the energy sector that offer subscription-based services with billing. A leading company in this sector turned to Moxoff to implement a tool that enables the identification of clients at risk of default as well as the most reliable ones, with the aim of optimising resources, improving credit management, and making loyalty and new prospect acquisition strategies more efficient.

Solution

At Moxoff, we have developed a predictive model based on Machine Learning techniques to estimate the likelihood that a customer will pay their bills on time. The system provides an accurate forecast of payment trends in the months following invoice due dates, supporting more informed and targeted strategic decisions.

Benefits

  • Resource optimisation: the platform enables a clear distinction between reliable clients and those potentially at risk, allowing the company to implement targeted and effective actions.
  • Cash flow management: payment forecasts for clients improve cash flow management and budget planning for future actions.
  • Scenario simulation: it allows for the analysis of information on customers creditworthiness and the prediction of future trends, supporting the development of targeted strategies, including for new user categories and emerging markets.
  • Improvement of customer loyalty: thanks to the insights provided by the software, the company can adapt its loyalty policies by proactively intervening with personalised offers and plans for at-risk clients, thereby improving their experience and reducing churn.
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