Financial Services & Neo4j: Fraud Detection
By Bryce Merkl Sasaki | June 19, 2017
Identifying and stopping fraudulent activity is harder than ever for financial services organizations. Standard anti-fraud technologies — such as a deviation from normal purchasing patterns — use discrete data. This is useful for catching individual criminals acting alone, but discrete… Learn More →
Keywords: Connected Data • cypher • Data Visualization • financial services • Fortune 500 • fraud detection • fraud ring • graph technology • Microsoft SQL Server • relational database
How Graph Databases Stop E-commerce Fraud in Real Time
By Bryce Merkl Sasaki | January 25, 2016
As our lives become increasingly digital, a growing number of financial transactions are conducted online. Fraudsters have been quick to adapt to this trend, and to devise clever ways to defraud online payment systems. While this type of activity can… Learn More →
Keywords: credit card number • e-Commerce Fraud • fraud detection • fraud patterns • fraud ring • fraud scenario • graph database • ip address • online payment systems • synthetic identities
Catching Insurance Fraud Using Graph Database Technology
By Bryce Merkl Sasaki | January 18, 2016
The impact of fraud on the insurance industry is estimated to be $80 billion annually in the US, a number that has been growing in recent years. From 2010 to 2012, questionable claims in the U.S. jumped 27 percent, to… Learn More →
Keywords: fraud detection • fraud ring • graph database • Insurance Fraud • Network Analysis • relational database • social network analysis • soft tissue injuries • whiplash
Improving First-Party Bank Fraud Detection with Graph Databases
By Bryce Merkl Sasaki | January 11, 2016
First-party bank fraud involves fraudsters who apply for credit cards, loans, overdrafts and unsecured banking credit lines, with no intention of paying them back. It is a serious problem for banking institutions. U.S. banks lose tens of billions of dollars… Learn More →
Keywords: bank fraud • cypher • first-party fraud • fraud detection • fraud prevention • fraud ring • graph database • graph traversal • link analysis • relational database
Why Modern Fraud Detection Needs Graph Database Technology
By Bryce Merkl Sasaki | January 4, 2016
Banks and insurance companies lose billions of dollars every year to fraud. Traditional methods of fraud detection play an important role in minimizing these losses. However increasingly sophisticated fraudsters have developed a variety of ways to elude discovery – both… Learn More →
Keywords: bank fraud • Connected Data • data analysis • e-Commerce Fraud • fraud detection • fraud prevention • fraud ring • graph database • Insurance Fraud • real-time fraud detection
Graph Databases in the Enterprise: Fraud Detection
By Bryce Merkl Sasaki | September 21, 2015
Banks and insurance companies lose billions of dollars every year to fraud. Traditional methods of fraud detection fail to minimize these losses since they perform discrete analyses that are susceptible to false positives (and false negatives). Knowing this, increasingly sophisticated… Learn More →
Keywords: banks • e-Commerce Fraud • fraud detection • fraud ring • Graph Databases • insurance company • link analysis • online payment systems • synthetic identities • use case
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