Spam filters are supposed to block e-mail scams from ever reaching us, but criminals have learned to circumvent them by personalizing their notes with information gleaned from the Internet and by grooming victims over time.
In response, a company called ZapFraud is turning to natural-language analytics: Instead of flagging key words, it looks for narrative patterns symptomatic of fraud. For instance, a message could contain a statement of surprise, the mention of a sum of money, and a call to action. “Those are the hallmark expressions of one particular fraud e-mail,” Markus Jakobsson, the company’s founder, told me. “There’s a tremendous number of [spam] e-mails, but a small number of story lines.” In the future, this technology could go beyond e-mail filtering to also flag text messages, interactions on social media, messages on dating sites, even years-long “friendships.” Aaron Emigh, ZapFraud’s interim CEO, told me he’d stopped a woman from wiring money to a “fellow widow” she’d met on a Christian site for grieving people. He hopes that as natural-language analytics evolves, such warnings can be wholly automated. A similar approach could help combat fraud by flagging false statements on social media.

Read more at The Atlantic