Category: blog

A retro analysis of your customer base helps identify financial risks by examining payment behavior and company characteristics. By combining data such as industry, company size and financial metrics, you gain insight into which customers are causing payment problems. These insights enable you to improve your credit policies and screening processes, identify risks early and adjust payment terms. So you better protect your organization from losses and make smart, data-driven financial decisions.

Credit management has transformed from manual and fragmented to automated and data-driven. Thanks to integrations with CRM and accounting systems, departments such as sales, marketing and compliance work with real-time customer insights. Through API links, essential credit data flows directly into internal systems, speeding up risk identification and making decisions more efficiently.

The Netherlands is introducing a new SBC code as of September 1, 2025. This may appear to be a purely Dutch update, but Belgian companies doing business with Dutch customers will also feel the effects. Do you use Dutch data for risk analysis, segmentation or reporting? Then this is the time to review your processes and systems.

From January 2025, the classification of Belgian sector codes (NACE-BEL) will change. The update provides a more modern classification of economic activities and has a direct impact on your data, analyses and systems. Think of changed risk models, CRM segmentation and data links. By anticipating now, you avoid mistakes and stay futureproof as an organization.

On June 6, 2025, Altares Dun & Bradstreet will launch an innovative Belgian AI scorecard for credit assessment. Powered by advanced neural networks and proprietary explainability methods, the model offers clear insight into every decision. Fully transparent, ethically designed, and compliant with GDPR and the EU AI Act. This scorecard enables organizations to assess risks more accurately and make responsible decisions in a rapidly evolving economy.