Australian banks pilot fraud intelligence sharing network


Australia's top banks are piloting a fraud and scams intelligence-sharing network using behavioural- and device-based technology from security vendor BioCatch.

ANZ, Commonwealth Bank of Australia, National Australia Bank, Suncorp Bank, and Westpac are all taking part in the pilot, which aims to tackle fraud and scams by assessing in real time the potential risks associated with accounts to which customers direct their domestic online payments. If the network identifies risks associated with a receiving account, BioCatch provides this intelligence to the sending bank in real time, allowing it to review the transaction before any money leaves the account. BioCatch Trust combines behavioural intelligence with digital session, payment, account, device, and non-monetary event intelligence to assess the potential risks of receiving accounts. This, says the firm, helps banks prevent those types of scams where the fraudster manipulates the victim via an email, text message, or social media post. CBA head of group fraud James Roberts says: "BioCatch Trust is the first time banks have been able to share information in real time before a payment is made. In a world-first, this will help protect Australians from losing money to scammers." However, echoing sentiments expressed by banks in the UK, Chris Sheehan from NAB says tech platforms and telcos need to do more to tackle fraud before it gets to the stage where the new BioCatch network is needed. In comments reported by Information Age, Sheehan says: "By the time BioCatch Trust is triggering an alert for us to act upon, someone’s already made a payment, or tried to make a payment — which means someone’s already received a scam text message or WhatsApp message, someone’s already clicked on a link that’s taken them to a fake investment scam on Facebook or Google. "We’ve got to do more, and those industries need to do more to get the bad content off their platforms and off their channels."


By on Thu, 21 Nov 2024 00:01:00 GMT
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