Month: October 2015

Cross channel scams are the most pervasive form of frauds perpetrated against bank customers. Fraudsters target customer accounts by a number of access points- branches, ATM, cards, online banking or wire transfers. With multiple channels leading to multiple access points, installing adequate combat mechanisms takes a backseat, thus expanding the attack surface. Consumers have been steadily using mobile phones, cards and Internet banking, mainly relying on good faith in financial institutions. But as scams become more complex and less predictable, banks need to keep a tight vigil against fraudsters targeting across multiple channels. Banks need to break free from the traditional ‘Starfish’ approach of combating fraud in silos; they need to actively base their combat mechanism on cross-pollinated intelligence that runs across multiple channels.

Let’s assume a scenario to better validate the above points.

Jamie is a budding photojournalist. She stays in a paying guest accommodation in Mumbai. She is an intern with a well-known magazine. Normally, she receives her salary on the last day of every month and pays her rent on the 1st. She saves the rest of her salary for paying off her expenses throughout the month and manages to save some money for her impending Euro trip. This time though, soon after her salary gets credited, there is an entire salary debit on 1st. By the time the bank and Jamie get to know about this fraudulent transaction, the entire money is lost. The bank fails to recognize this transaction as a fraudulent one.

The scenario discussed above could have easily been averted had the bank implemented a unified cross-channel fraud management system. Jamie wouldn’t have lost her salary. The bank wouldn’t have let the abnormal transaction to go through without additional levels of authentication across different channels.

Traditional fraud management solutions employed by banks have silo based systems that have the ability to monitor and detect fraud only for a single channel/product at a time e.g. credit card fraud detection, Internet banking fraud detection etc. Even the systems credited for being multi-channel managed frauds on multiple channels but not across multiple channels. An ideal cross-channel fraud management solution not just monitors and prevents fraud on multiple channels but also has the ability to correlate the intelligence gathered from one source system to the events happening on other channel to detect and prevent fraud.

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