Fraud rarely happens in a vacuum.<\/p>\n\n\n\n
On one end of the spectrum are fraud rings<\/a>, which are essentially organized gangs of criminals who collaborate closely to carry out wire fraud<\/a>, mail fraud, payment card fraud, and other financial crimes. On the other end are the \u201clone wolves,\u201d who carry out fraud attacks on their own.<\/p>\n\n\n\n But, even scammers who act alone don\u2019t truly do everything <\/em>by themselves. For example, they may learn and share fraud tactics on the internet, buy compromised logins or card numbers<\/a> on the dark web, or recruit unwitting accomplices using social media.<\/p>\n\n\n\n Even the most diligent and privacy-minded scammers are going to leave behind some kind of trail. When they do, link analysis might help expose their activity.<\/p>\n\n\n [noun]\/liNGk \u2022 \u0259 \u2022 nal \u2022 \u0259 \u2022 s\u0259s\/<\/p><\/div> Link analysis is a forensic technique that examines the connections, relationships, and dependencies between individuals, accounts, addresses, devices, IP addresses, payment cards, transactions, and other entities or events for possible signs of fraudulent behavior.<\/p><\/dd><\/div><\/dl>\n\n\n\n Essentially, link analysis provides context to fraud. Rather than examining a single <\/em>device or individual\u2019s involvement in fraudulent activity, link analysis allows you to look at relationships between <\/em>actors for evidence of overlap.<\/p>\n\n\n\n Link analysis can be performed using graph networks, a type of database that lets you visualize connections (represented via edges) between entities (represented via nodes). This way, you can see how the instances of first-<\/a>, second-<\/a>, or third-party fraud<\/a> you encounter are related to each other.<\/p>\n\n\n\nRecommended reading<\/h3><\/div>
What is Link Analysis?<\/h2>\n\n\n\n
How Graph Networks Detect Fraud<\/h3>\n\n\n\n