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.
