As your organization faces ever tougher sustainability regulations, you need new solutions to stay compliant. Thankfully there is advanced technology at hand.

One regulation you will have to battle with if you operate in Europe is the EU’s Carbon Border Adjustment Mechanism (CBAM). It is designed to curb carbon leakage by placing a carbon price on imports of certain goods from non-EU countries.

Complying with CBAM is not just a regulatory checkbox – it is also an opportunity to show the world that your organization takes environmental stewardship seriously. And in this blog post we will uncover a new solution that simplifies this.

Stibo Systems and Nexer have teamed up to build a powerful AI-driven solution that helps organizations meet this regulatory challenge. Their solution uses the master data management (MDM) platform from Stibo Systems, infused with machine learning (ML) capabilities.

The solution simplifies CBAM compliance by assisting in accurate product classification and carbon reporting – an area where traditional manual processes often fall short.

The challenges CBAM poses

CBAM will reshape how businesses handle imported goods within the EU. Anyone importing products from non-EU countries needs to classify their goods according to the Combined Nomenclature (CN) and calculate their associated carbon emissions.

The classification process involves managing huge datasets and highly complex regulatory structures. So, if your business handles large inventories, the challenge is clear: manually assigning products to their correct classifications is:

• time-consuming
• labor-intensive
• Error-prone

This is where the Stibo Systems and Nexer solution comes in. The two partners have a history of collaboration and co-creation, and here the focus is on incorporating ML into Stibo Systems' MDM solution, thereby assisting and improving the above process.

Using AI to address classification and compliance

The model developed by Nexer and Stibo Systems uses unsupervised and supervised learning, enabling both initial classifications and improved model confidence, as more data becomes available.

This is crucial when you need to classify goods based on CN codes – where even small errors can lead to compliance failures and penalties.

Unsupervised learning

The unsupervised model processes large datasets and helps predict classifications by analyzing the hierarchical structure of CN codes. It can provide an initial classification, which is especially useful when you don’t have historical data or when you are dealing with new products.

Supervised learning

As the amount of historical data increases, the supervised model can further refine classifications by training on items that are already classified. This method further improves accuracy, making it even easier to be compliant.

In other words, both models work together in a “stacked” approach. Data managers can switch between the two depending on the confidence levels in the predictions. This makes the classification process both flexible and precise.

Enhancing MDM for sustainability

If you are a Chief Sustainability Officer, this approach is particularly useful. Not only will you manage your organization’s data more effectively – you will align your operations with broader sustainability goals.

The AI-powered MDM platform can quickly adapt to regulatory changes, giving you a future-proof tool that evolves with new requirements, like CBAM. The solution also enhances transparency and traceability – key factors in corporate sustainability.

By ensuring your carbon reporting and product classifications are accurate, the system helps you maintain accountability throughout your supply chain, bolstering your sustainability credentials.

Looking ahead to the future of data-driven compliance

As regulations like CBAM become the norm, you can make compliance a whole lot easier at a strategic level by using solutions that integrate sustainability into every layer of operations.

With this particular solution, the use cases don’t even stop at managing sustainability compliance. You can also use it to monitor the amount of tax you should pay on goods you import from outside the EU.

So, the solution by Stibo Systems and Nexer sets a strong precedent. It shows you can use advanced technologies like machine learning to solve complex regulatory (and other) challenges. Use your MDM solution to both stay compliant and efficient – and advance your sustainability agendas.

About Nexer

Nexer is a global tech company with strong roots in the Swedish heritage of entrepreneurship and innovation, that drives digital transformation across industries by leveraging cutting-edge technologies and sustainable solutions. Nexer has been a trusted implementation partner of Stibo Systems since 2011, and as experts on the Stibo Systems STEP platform they help organizations improve data quality and manage their master data for further business growth. Nexer offers comprehensive MDM solutions, including system implementation, integrations, configuration, application management services (AMS) and staff augmentation on Stibo Systems STEP as well as data management strategy consulting. These services empower companies to streamline their operations and achieve their business goals by ensuring accurate, accessible, and well-governed data throughout their business processes including sustainability data.

Learn more about Nexer and Sustainability Data Management.