Most (76%) provide simple identification of account holders' devices, such as computers or smart phones, often by using cookies stored in the browser from previous transactions or by verifying a user's IP address. A 76% majority also conduct knowledge-based authentication, for example by asking the accountholder to answer security questions. Rules-based fraud detection — software that uses rules engines and analytics to identify potential fraud — is used by 59%, as are email or SMS transaction alerts to accountholders that give them a chance to verify or decline. Digital certificates are used by 53% of banks to authenticate the identity of the person making a transaction. Just over half (53%) also use one-time passcode tokens.
Some less common fraud prevention tools are on many banks' drawing boards. Today only 24% use neural network-based fraud detection, but 47% plan to deploy this technology, which uses computer learning to build up knowledge of transaction patterns that indicate potential fraud, within in the next 12 months. Similarly, 24% of banks today provide out-of-band authentication, in which the bank verifies a transaction through a different channel; but 47% plan to deploy such technology in the next 12 months. Complex device identification, which uses techniques such as geolocation to confirm a transaction is originating from the accountholder's location, is currently used by 12% of banks but is planned for the next year at 35% of banks.
Despite all these efforts, only 6% of bankers surveyed believe their fraud prevention and detection tools can detect cross-channel fraud patterns. Fifty-nine percent say their current technology is "somewhat" able to detect such fraud, but 35% say their tools do not detect cross-channel fraud.
Overall, 71% of the bankers surveyed said lack of resources keep them from effectively detecting and preventing fraud. They also expressed frustration at consumer ignorance of fraud - 53% said lack of customer awareness is a barrier to fraud detection.
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