Introduction
Entity resolution underpins many of the most powerful fraud detection capabilities available to insurers today. Without it, risk remains fragmented across systems, policies, and claims, making organised and repeat fraud difficult to identify.
As fraud becomes increasingly networked, accurate entity resolution is no longer optional.
What Entity Resolution Means
Entity resolution is the process of determining when different records refer to the same real-world person, organisation, device, or asset. Variations in spelling, formatting, or identifiers often mask true connections.
For example, a single individual may appear under slightly different names or addresses across multiple policies or claims.
Why Entity Resolution Matters
When entities are not resolved correctly:
- Risk appears isolated rather than cumulative
- Repeat behaviour is missed
- Network analysis becomes unreliable
- Investigations are slower and less effective
Accurate resolution allows insurers to see the full risk picture.
Entity Resolution in Practice
Modern entity resolution combines:
- Deterministic matching (exact rules)
- Probabilistic matching (likelihood-based)
- Contextual signals (behaviour, timing, relationships)
This layered approach balances accuracy with flexibility.
Supporting Network and Link Analysis
Entity resolution is the foundation for network analysis. Without reliable entities, relationship mapping produces incomplete or misleading networks.
Strong entity resolution enables investigators to uncover fraud rings, collusion, and repeated patterns that would otherwise remain hidden.
Related Topics
Network analysis
Link analysis
Entities of interest
Data quality
