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Entity Resolution

Overview

Entity resolution is the process of identifying, matching, and consolidating records that refer to the same individual, business, or organization across multiple databases and systems. It helps organizations create a single, accurate view of an entity by resolving duplicates, inconsistencies, and fragmented data. This is especially important in compliance, where incomplete or mismatched records can lead to regulatory breaches, fraud, or missed risk signals.
For banks, fintechs, insurers, and regulators, entity resolution enables reliable Know Your Customer (KYC), Know Your Business (KYB), and anti-money laundering (AML) processes. It typically uses algorithms, fuzzy matching, probabilistic models, and increasingly AI-driven techniques to link records based on names, addresses, identifiers, and behavioral patterns. By unifying records, organizations strengthen risk assessment, streamline onboarding, and enhance operational efficiency, while ensuring they meet regulatory obligations for accurate reporting and customer due diligence.

FAQ

Why is it hard?

Variations, transliterations, and outdated data cause near-duplicates. Balancing precision/recall without losing explainability is the core challenge.

What improves results?

Standardization, weighted attributes, contextual signals (device/IP), and feedback loops from reviewer outcomes.

How does it aid screening?

By consolidating identities so sanctions/PEP matches hit correctly, reducing both misses and noise.

What governance is needed?

Track provenance, decisions, and thresholds; enable rollback and re-merge policies with audit trails.