Link analysis for fraud detection

How our technologies help to detect and investigate fraud

Fraud: the data challenge

Fraud is an expensive and complicated problem. To do fraud detection well, you need to see connections – between people, accounts, transactions, and dates.

It’s further complicated by the fast-changing tactics used by fraudsters. As their crimes become more sophisticated, so too must the data analysts’ tools. This means relying on a lot of data and fraud detection tools powered by link analysis.

Fraud detection & investigation tools

Discover five ways link analysis helps fraud detection and investigation.

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The link analysis solution

When detecting fraud, analysts look for two types: known and unknown fraud.

Fraud detection and investigation techniques are used to uncover known and unknown fraud
Fraud detection and investigation techniques are used to uncover known and unknown fraud

As the names suggest, ‘known fraud’ is fraudulent activity that has been encountered before. The behavior patterns can be defined and detected with rule-scoring and pattern-matching (‘pattern of life’) algorithms. In this case, link analysis plays an investigative role, providing fast and accurate situational analysis and informing a go / no-go decision.

Conversely, ‘unknown fraud’ has not been previously encountered. As automated processes will not help here, link analysis acts as a fraud detection tool.

Investigations of known fraud tend to take a case-centric approach – starting from a specific transaction, account or person, and working outwards. We can see that approach in action in this blog post about insurance fraud.

Unusual connections in an insurance fraud investigation
Looking for known fraud patterns in an insurance fraud link analysis example

Investigations of unknown fraud use a global approach – loading large volumes of transactions into a chart to uncover outliers or unusual patterns.

Using a global approach to uncover unusual patterns that could indicate previously 'unknown' fraud
Using a global approach to uncover unusual patterns that could indicate previously ‘unknown’ fraud

Why choose us?

Fraud data is large, complex, noisy and often incomplete. Link analysis helps analysts investigate fraud in an interactive and intuitive way.

Our technologies can help analysts:

  • Join the dots in fraud data to discover patterns and anomalies
  • Pull transaction data from multiple sources
  • Share interactive charts for reporting and investigation
  • Make informed decisions more quickly

Our toolkits also include advanced functionality to help analysts unlock fraud data and see context on demand, including filtering, layouts, social network analysis, time analysis and geospatial visualization.

Find out more

We work with organizations, including Visa, Aviva, Cifas and JPMC, to help them make sense of complex connected data for fraud detection and investigation. If you’d like to learn more, request a trial of our technology.

Try our technology

Fraud-webinar
Webinar: Fighting Fraud with Graphs