Three Reasons Traditional Machine Learning Can't Stop Multi-Channel Bank Fraud Global Banking & Finance Review

Financial institutions are learning the hard way what can happen when criminals get their hands on the latest technology. Gone are the days of robbing tellers at gunpoint; today's sophisticated criminal networks and nation-states use machine learning and artificial intelligence to target institutions remotely, quietly and through many channels at once. They have figured out banks' vulnerabilities and exploited them mercilessly through a combination of malware, ATM jackpotting, money mules, money laundering, e-payment/cryptocurrency fraud and more, stealing untold millions to finance terrorism and profit from human and drug trafficking. So, what exactly is "cross-channel fraud"? A perfect example can be seen in the tremendously successful Carbanak campaign, which used cross-channel methods to steal more than a billion euros from over 100 banks in 40 countries.