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How AI fights fraud in the telecom industry


Over 59 million Americans said they lost money as a result of phone scams in approximately the past 12 months, with an average reported loss of $502, according to the Truecaller Insights US Spam & Scam Report. "Fraud is a major consideration in the telecom industry," said Dr. Gadi Solotorevsky, CTO at Amdocs cVidya, an AI solutions provider. "Today, close to 2% or over $1.5 trillion in yearly global revenue is lost annually due to fraudulent behavior. The total losses across the industry are staggering." Solotorevsky cited a 2019 survey from the Communications Fraud Control Association (CFCA) that found that two-thirds of respondents experienced an increase in fraudulent activities. "We mostly encounter payment and subscription fraud, identify theft/impersonation, account takeover, insider threats, and SIM swap," Solotorevsky said.

Machine Learning Techniques for Fraud Analytics, Part 1 ThreatMetrix


Fraud analytics is an endless game of cat and mouse, but machine learning just might be the tool to help fraud professionals win this game.

Why Ad Fraud Keeps Battering Brand Safety


The exact numbers remain murky, but according to estimates from TrafficGuard/Juniper, the financial toll ad fraud levies on marketers may be as much as $3 billion a month. I recently asked Tony Marlow, CMO of Integral Ad Science, a digital ad verification firm, to update us on the latest ad fraud skirmishes. Paul Talbot: Of all the reasons why ad fraud persists, which one is the most significant? Tony Marlow: Brands are shifting bigger budgets into digital advertising, with recent estimates expected to top $455 billion this year. When it comes to ad fraud, that means the stakes are higher than ever.

How Machine Learning Combats Payment Fraud


Payment fraud evolves in ways that are truly frightening -- and with haste. Fraudsters are continually scrambling to keep up with, and have one foot in front of, technology, with recent stumbling blocks in the form of EMV, in the United States, likely to give rise to greater card-not-present fraud. But the would-be payments criminals have potent weaponry at hand, including ever faster, ever more powerful and ever cheaper computing power, and they have been targeting, according to data science firm Feedzai, the weaker links that exist in the financial services chain. In a recent whitepaper titled "A Primer to Machine Learning for Fraud Management," the firm noted that, even as financial services evolve to embrace a digital world -- with, say, virtual goods in hand and even virtual cash -- the prospects for successful payments malfeasance grow in lockstep. In fact, said Feedzai, as many as 65 percent of firms with annual revenues of at least 1 billion were victims of payments fraud as recently as 2014.