Quantexa uses Entity Resolution – a data matching method that reasons like a human, using all available data and many different ways of linking records.  

That is why our solution can make connections between records and enrich your data, even when quality is poor. For example, our solution demonstrated 99% data matching accuracy in an independent test with Dun & Bradstreet. More about Quantexa’s Entity Resolution can be found here.  

 Our Entity Data Quality solution can help you improve data quality by identifying inconsistencies and flagging data remediation opportunities.  

Rules-based transaction monitoring systems have several limitations and challenges, which have historically hindered their effectiveness in detecting and preventing integrity risks.   

For example, the rules and thresholds need to be manually created and updated, making the system less adaptable to evolving and emerging threats.  Similarly, rules-based systems also typically analyze individual transactions in isolation and may not provide a comprehensive view of supplier relationships.  

In contrast, by combining multiple internal and external data sets all at once, Contextual Monitoring transforms the view of risk to a gain clearer understanding of multi-tier supply chains, their relationships and behaviors in real time. Using advanced entity resolution and network generation techniques, Contextual Monitoring focuses on holistic relationships rather than transaction risk in isolation.  

This added context helps to identify hidden risk and generates fewer, more accurate alerts. Institutions can reduce rising compliance and operational costs and conduct more effective and efficient intelligence-driven risk processes without replacing existing systems.  

Whilst the use case and risk coverage will largely determine the data needs, to generally better detect and investigate integrity risks within the Supply Chain, you would need access to various types of data from multiple trusted sources – consolidated into a single source for monitoring, detection and investigation purposes.   

 Here are just some key data types that can be valuable in detecting integrity risks. However, as part of any engagement Quantexa will help guide you to ensure you use only the data that’s required:  

• Supplier data (Contracts, Invoices, PO’s, Payments etc) 

• Customer data  

• External / third-party data (corporate registries, government databases, watchlists, sanctions lists, public records, adverse media, etc.)  

• Compliance data   

Quantexa solutions are built with flexibility, agility and self-sufficiency in mind and can be implemented incrementally. We integrate seamlessly with existing systems and can augment technology and processes already in place. We can iterate our approach with more capabilities and use cases to yield consistent, substantial value across your enterprise as our relationship evolves. We also design solutions for seamless integration to industry standard case manager tools including Oracle Mantas, Appian and Actimize.  

Traditional risk detection technology tend to be one-dimensional generally looking at only internal or only external data in isolation. 

By bringing in more context, and mapping a contextual view of the enterprises supply chain there is a much richer view of risk. 

Quantexa prides itself on its open architecture and its ability to integrate seamlessly into existing systems.