Detecting eCommerce Fraud with Neo4j and Linkurious
Last year, the global eCommerce market represented $1.9 trillions. As the market expands worldwide, the opportunity for fraud keeps growing with fraudsters constantly refining their tactics to outsmart anti-fraud frameworks. From chargeback fraud to re-shipping scam or identity fraud, numerous types of fraud can impact your organization. While collecting data is essential to enable real-time risk assessment, many organizations don’t have the necessary tools to find the insights needed to block fraud attempts. Neo4j and Linkurious offer a solution to tackle the eCommerce fraud challenge. Their combined technologies provide a 360° overview of organization’s data and allow real-time analysis and detection of eCommerce fraud patterns and activities.
Detecting eCommerce Fraud with Neo4j and Linkurious
- 2. ? Intro ? Graph technologies ? eCommerce Fraud ? Detection technical challenges ? Benefits of using Linkurious & Neo4j ? Demo ? How it works ? Use case ? Q&A “ ” Elise is a Marketing Project Manager at Linkurious. She works with Linkurious' partners to cover the emerging graph technology use cases. “ ”
- 7. Friendly fraud Affiliate fraud Account takeover Identity theft Reshipping fraud Promotion abuse Phishing Merchant fraud
- 8. eCommerce merchants loose 1.39% of revenue to fraud in average, which accounts for billions of dollars worldwide. Juniper, ”Online payment fraud whitepaper 2016-2020”.
- 9. Gartner Inc, “The conceptual model of a layered approach for fraud detection” in Market Guide, Online Fraud Detection: A Layered Approach