An unbeatable customer acceptance process thanks to mixed data (NL)

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As a credit manager, it is important to be involved in the customer acceptance process. After all, accepting new customers involves many risks. By choosing a strategy in which you preventively determine the creditworthiness of potential customers and continue to monitor them, you build up a high-quality customer portfolio. By combining your own company data with external data, you collect enough valuable information about the creditworthiness of a customer. But what actions should you take when mapping risks? In this paper we describe how, by using mixed data, you can minimize credit risk.

  • Examples from the field

    We show through a real-life example why mixed data is essential to your customer acceptance process.
  • 7 steps to minimize credit risk for your business

    In this paper, we have formulated 7 steps that are indispensable in the customer acceptance and monitoring process. Follow the steps to minimize credit risk.
  • This is how you use mixed data

    In this paper, we describe how using mixed data can reduce credit risk and ultimately even increase revenue in a more sustainable way.

10 pages

10 minute read

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