top of page

PRODUCT

Introducing
SEIA's PERCEIVE -
Data Quality Assessment

A Risk Cognition Solution that uses advanced data analytics to help you evaluate the integrity of your internal data and identify data quality issues exposing your company to compliance risks

Screenshot_2024-10-24_at_13.47.36-removebg-preview.png

PERCEIVE the regulatory risks your data quality poses

Data quality cleanup projects are often incredibly cumbersome, expensive, and time-consuming, frequently taking years to complete. During this lengthy process, new data issues can emerge, leading to an endless cycle of addressing old problems while new ones arise. This constant churn makes it difficult to maintain consistent data integrity. Without a proactive, continuous data quality management approach, companies risk falling into a costly and never-ending cycle of remediation.

At SEIA, we integrate relevant internal sources of data and leverage advanced data analytics to identify and prioritize data quality issues based on their criticality. Not all data issues are equally urgent; for example, missing a classification for the export of apples from Germany to France might not raise alarms, but missing a classification for a potentially controlled item heading to Iran is a serious compliance risk.

By identifying the most pressing data quality issues, we enable companies to prioritize their efforts where it matters most, helping them focus on areas that expose them to compliance risk and require immediate attention. This targeted approach ensures efficient use of resources and significantly reduces risk.

A first of it's kind Risk Cognition™ Solution

Learn more about our technical approach to leveraging the data you already have to ensure you manage what you already know. 

Key Benefits

Get more value from existing investments:

Data quality is critical in trade compliance because it directly impacts the effectiveness of the IT infrastructure that companies heavily invest in. These systems rely on accurate internal data to function properly. Poor data quality can undermine the value of these investments, while improving data quality ensures that these solutions can operate at their full potential

Communicate with authorities based on reliable data:

Companies regularly apply for licenses and interact with government authorities, basing their submissions on internal data. Inaccurate or incomplete data can result in delays, rejections, or compliance breaches.

Conduct Risk Assessments based on internal data:
High-quality data is also crucial for identifying compliance red flags, as risk assessments heavily rely on internal data to highlight potential areas of concern. Without reliable data, companies could overlook critical risks, leading to costly non-compliance and business interruptions.

Avoid costly penalties and fines:
Accurate data ensures compliance with trade regulations, reducing the risk of costly fines, penalties, or delays at customs due to incorrect or incomplete information.

Ensure Efficient Supply Chain Operations: 

Poor data quality can lead to shipment delays, incorrect customs filings, or export hold-ups. Reliable data helps streamline supply chain processes, ensuring goods move efficiently across borders without unnecessary interruptions

bottom of page