When entity resolution systems identify multiple records as the same business or customer entity, they can inadvertently create new data quality problems. One of the most persistent challenges? Inconsistent entity data that creates confusion, compliance risks, and poor decision-making. Today, we announce a new solution: Tilores' new Consistency feature.
The Hidden Cost of Inconsistent Entity Data
Picture this scenario: Your entity resolution system identifies three company records as the same business entity based on matching company names. However, due to pair-wise matching logic, this single entity now contains three different VAT numbers. Suddenly, your "clean" data becomes unreliable for:
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Compliance reporting - Which VAT number is correct for regulatory filings?
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Financial analysis - How do you reconcile transactions across multiple tax identifiers?
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Customer management - Sales teams receive conflicting information about the same client
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Risk assessment - Credit decisions become challenging when entities have multiple inconsistent identifiers
This creates a fundamental trust problem with your data that ripples through every business decision.
Introducing Consistency: Business Intelligence You Can Trust
Tilores' new Consistency feature solves this challenge by ensuring that critical attributes remain consistent across all records within a single entity. Unlike traditional pair-wise matching that can create these inconsistencies, our consistency rules validate that essential identifiers—like VAT numbers, social security numbers, or license IDs—remain unique and consistent within each resolved entity.
The key insight is that consistency requirements vary by identifier type. While it's perfectly acceptable for a company entity to have multiple customer IDs from different systems, having multiple VAT numbers indicates a data quality problem. The Consistency feature is designed to be applied selectively—you configure it only for those identifiers where duplicates signal incorrect matching, not for those where multiple values are expected and legitimate.
Real-World Business Impact
For Financial Services
Banks using Tilores for customer due diligence can now ensure that each customer entity has only one social security number, eliminating the risk of accidentally merging different individuals' financial profiles. This reduces compliance violations and improves regulatory reporting accuracy.
For B2B Companies
Enterprise sales teams can trust that each company entity has a single, consistent VAT number, enabling accurate invoicing, tax reporting, and financial forecasting. No more manual verification of conflicting tax identifiers.
For Healthcare Organizations
Patient safety improves when medical records ensure consistent patient identifiers. The consistency feature prevents dangerous scenarios where multiple patients might be merged due to similar names while maintaining different medical record numbers.
Why Consistency Rules, Not Just Matching Rules?
You might wonder why we created a separate consistency feature instead of simply using matching rules. The answer lies in how pair-wise matching works versus entity-wide validation.
Consider these three records for "John Smith":
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Record A: Has SSN "1234567890"
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Record B: Has no SSN
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Record C: Has SSN "0987654321"
With traditional matching rules, Record A matches with Record B (same name, no conflicting SSN), and Record B matches with Record C (same name, no conflicting SSN). Through this chain, all three records end up in the same entity—even though Records A and C have different SSNs.
Consistency rules solve this by evaluating the new record against all existing records in the potential target entity. When Record C is being processed, the consistency rule checks it against both Records A and B. Since Record C conflicts with Record A's SSN, the entire entity is rejected as a match, preventing the inconsistent merge.
How It Works: Smart Validation Without Performance Sacrifice
The Consistency feature operates intelligently:
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Validates during entity resolution - Before adding a new record to an entity, the system checks all existing records within that entity
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Handles missing data gracefully - Records without certain identifiers can still be matched, maintaining flexibility
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Optimized for performance - Internal optimizations ensure consistency checking doesn't slow down your resolution process
Check our technical docs for detailed information about how to use this new feature.
The Bottom Line: Better Decisions Through Better Data
With Tilores' Consistency feature, organizations can:
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Reduce manual data validation efforts significantly
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Improve compliance accuracy with consistent regulatory identifiers
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Accelerate decision-making with trustworthy, consistent entity data
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Minimize operational risk from data inconsistencies
Getting Started
The Consistency feature is available now for all Tilores customers. Our team is ready to help you configure consistency rules tailored to your specific use case and data schema.
Ready to eliminate data inconsistencies and unlock reliable business intelligence? Contact our team to learn how the Consistency feature can transform your entity resolution process.
Tilores is the modern entity resolution platform that helps organizations create a single source of truth from fragmented data. Learn more at tilores.io
