Entity Resolution and Network Analysis for Financial Crime Detection
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Key Insights
- Financial crime networks are sophisticated, using shell companies, nominees, and layered structures to obscure beneficial ownership.
- This module covers entity resolution techniques (deterministic matching, probabilistic matching, machine learning-based resolution), network/graph analysis for uncovering hidden relationships (community detection, centrality analysis, link prediction), the application to beneficial ownership transparency, and 2025-2026 trends including the rise of graph databases in AML, corporate register integration via the Beneficial Ownership Data Standard, and AI-driven entity resolution at scale.
Overview
Entity resolution is the process of determining whether multiple records or identifiers refer to the same real-world entity. In AML compliance, entity resolution is critical for identifying related accounts, beneficial ownership structures, and hidden relationships that may indicate money laundering or sanctions evasion.
Network analysis extends entity resolution by mapping relationships between entities — individuals, companies, accounts, and transactions — to reveal hidden structures. Graph algorithms can identify suspicious patterns like circular transactions, concentration of funds, and unusual connectivity that may indicate organized criminal activity or terrorist financing networks.
Key Concepts
- Entity Resolution: The process of matching and linking records that refer to the same real-world entity across different data sources.
- Graph Database: A database that stores entities as nodes and relationships as edges, optimized for relationship queries.
- Social Network Analysis: Analyzing relationships between entities to identify key actors, clusters, and communication patterns.
- Circular Transaction Detection: Identifying transactions that flow through multiple accounts and return to the originator, indicating potential layering.
- Link Analysis: Visual and analytical techniques for discovering relationships and patterns in connected data.
Key Takeaways
- Entity resolution links records across systems to build complete customer profiles.
- Network analysis reveals hidden relationships and patterns invisible to transaction-level monitoring.
- Graph databases enable efficient querying of complex entity relationship structures.
- Circular transaction patterns may indicate money laundering layering activity.
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Feynman Concept Cards
Master each building block: read the ELI5, explore the analogy, work the example, find your gaps, teach it back, build it.
Entity Resolution is a concept in advanced techniques. In simple terms, Entity Resolution covers advanced techniques in Compliance. This compliance concept addresses key topics in the advanced techniques in compliance domain. Also known as: entity matching, record linkage
Analogy
Example
Find Gaps
Explain Entity Resolution as if teaching a colleague who is new to advanced techniques. Cover: what it is, how it works, and why it matters.
Create
Create a diagram that demonstrates Entity Resolution in a real-world advanced techniques scenario. Walk through your design decisions.
Show solution
A diagram for Entity Resolution should include: 1. The core components of entity resolution 2. How they interact 3. Expected outcomes or outputs
Beneficial Ownership is a concept in regulations. In simple terms, Beneficial Ownership covers regulatory frameworks in Compliance. This compliance concept addresses key topics in the regulatory frameworks in compliance domain. Also known as: UBO, ultimate beneficial
Analogy
Example
Find Gaps
Explain Beneficial Ownership as if teaching a colleague who is new to regulations. Cover: what it is, how it works, and why it matters.
Create
Create a diagram that demonstrates Beneficial Ownership in a real-world regulations scenario. Walk through your design decisions.
Show solution
A diagram for Beneficial Ownership should include: 1. The core components of beneficial ownership 2. How they interact 3. Expected outcomes or outputs
Suspicious Transaction Report is a concept in sar str. In simple terms, Suspicious Transaction Report covers suspicious activity reporting in Compliance. This compliance concept addresses key topics in the suspicious activity reporting in compliance domain. Also known as:
Analogy
Example
Find Gaps
Explain Suspicious Transaction Report as if teaching a colleague who is new to sar str. Cover: what it is, how it works, and why it matters.
Create
Create a flowchart that demonstrates Suspicious Transaction Report in a real-world sar str scenario. Walk through your design decisions.
Show solution
A flowchart for Suspicious Transaction Report should include: 1. The core components of str 2. How they interact 3. Expected outcomes or outputs
Feynman Synthesis — Prove You Understand
1. The One-Pager
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2. The Gap Map
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Flashcards
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