Fraud Prevention with Neo4j: A 5-Minute Overview
By Bryce Merkl Sasaki, Aspiring Graphista | April 21, 2017
Fraud is becoming increasingly difficult to discover and prevent as fraudsters are increasingly employing complex techniques and advanced technologies to perpetrate fraud. Who Are Today’s Fraudsters? Today, fraudsters are organized in groups, possess synthetic or manufactured identities – which in… Learn More →
Keywords: credit card fraud • data science • ecommerce fraud • financial services • fraud detection • fraud pattern • fraud prevention • Fraud Rings • Insurance Fraud • pattern analysis
Improving First-Party Bank Fraud Detection with Graph Databases
By Bryce Merkl Sasaki, Aspiring Graphista | 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, Aspiring Graphista | 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
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