Johan Bierebeeck (GraydonCreditsafe): The power of structured data in risk management
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Johan Bierebeeck, Country Manager at GraydonCreditsafe, outlines how structured data fuels business intelligence, compliance and risk management in a world driven by digital transformation.
Why does quality matter more than quantity in corporate data?
The common misconception that more data leads to better insights often misleads organisations. I always stress the priority of accuracy over volume. In practice, low-quality data burdens systems and teams with rework and correction, offsetting any advantage gained. Structured financial statements offer a solid foundation: they reflect the company's reality and allow reliable predictions. Through annual accounts, businesses can model resilience, for example how long a firm can survive market shocks based on available cash reserves. Covid provided a concrete test of that. We also assess solvency and detect inconsistencies or signs of hidden financial instability. What I frequently see is that too many firms chase datasets without verifying their origin, reliability or timeliness. Focusing on fewer, highly structured documents, such as official financials, lets companies train predictive models and reduce errors. Instead of compiling vague profiles, a deep dive into dependable data reveals which clients can survive a downturn, honour payments or meet regulatory requirements. Good data creates trust and confidence. It avoids the chaos of decision-making based on incomplete or outdated records. In short, better data, not more data, determines competitive advantage today.
How can companies access and process public information more efficiently?
Although public data like Luxembourg balance sheets should be easy to retrieve, that is often not the case. The LBR website now includes complex captchas and technical barriers, which make automation difficult. However, APIs provide a workaround. LBR offers at least two APIs: one gives general company information (registration dates, legal status, activity code) and another delivers daily publications, including structural changes and shareholder data. These often come as PDFs, which traditionally required manual reading. Now, artificial intelligence can extract insights from these unstructured documents. In our projects, we apply AI to scan annexes of annual accounts, looking for participation data and foreign affiliations. This helps track geopolitical exposures. The result is about 80 percent accuracy. While AI manages the bulk, 20 percent still needs human validation, especially when data is incomplete or format inconsistencies occur. Compared to older tools like Python, which fail with slight format shifts, AI adapts better to contextual understanding. The shift from manual data stewardship to automation allows us to handle massive volumes without compromising compliance. This ensures updated, accessible and actionable information, which is essential in today’s fast-moving, regulated environment.
“It is better to have better data than more data.”
What role does data play in identifying beneficial owners and hidden structures?
Transparency around beneficial ownership remains a critical challenge. A few years ago, Luxembourg’s public register offered clear access. That changed after legal challenges, leaving gaps in compliance workflows. However, it remains possible to rebuild the picture. By analysing shareholding structures and cross-referencing them across jurisdictions, one can identify patterns. For instance, in SARL structures, associés must be listed. If someone holds over 50 percent, then they are clearly the beneficial owner. The process becomes harder with SAs or foreign shareholders. That is where our international network becomes vital. GraydonCreditsafe operates data factories in sixteen countries and covers over two hundred jurisdictions. By linking across databases, we reconstruct networks of control and influence, similar to how hidden LinkedIn connections can be inferred through mutual visibility. This type of deduction is not always 100 percent reliable, but it forms a strong base for compliance officers facing strict regulatory obligations. Instead of rejecting potential clients out of fear or uncertainty, decision-makers can rely on reconstructed datasets to make informed choices. The more visibility they gain, the more efficiently they manage risks and partnerships.