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Why Machines Still Need Humans To Stop Identity Fraud

Why Machines Still Need Humans To Stop Identity Fraud

Right now, the banking and financial services sector is facing a critical juncture.

SwissCognitiveDigital tools have become one of the only means by which consumers can communicate with their banks and other financial services, even when opening brand new accounts. The pandemic has put trust in remote digital onboarding centre stage.

It’s not just banking. Government benefits, health services, online education, dating companies and gaming are just some of the sectors witnessing a huge surge in demand for digital know-your-customer (KYC) services. This is expanding the use of digital authentication at an unprecedented scale. Unfortunately, at the same time, the outbreak is proving fertile ground for fraudsters looking to exploit this global rise in digital metamorphosis.

The man behind the machine

Even in 2020, as economies digitise fast, most forms of identity globally are stuck in the analogue world. The fact is, as of today there is no comprehensive, interoperable digital identity that exists anywhere. To make things worse, fraudsters are hot on our heels creating fake IDs – each year, an estimated 20 percent of the techniques they deploy are new.

Right now, trust is paramount. You need to trust a system that’s going to take physical identity documents and live images of real people and turn them into digital identities. But it’s not possible to account for all types of this ‘ingenious’ fraud in an automated system.

The science behind digital authentication has become more complex and certainly more automated than ever before. Machine learning algorithms can digest multiple security features in a passport or driving licence and know whether it’s fake. This combined with the ubiquity of smartphones can verify the consumer using a selfie and liveness detection, which recognises whether a person is real.

It’s true that fully automated systems can be faster. -powered technology can recognise valid ID as genuine, and match the ID photo with a selfie using biometric facial comparison. But while algorithms are powerful, they are not perfect. will need volumes to become better. There will be exceptions that the technology has not yet been trained to recognise.

And as fraud techniques arise quickly, we still need real-life experts. We need a trained human-eye, and sometime multiple pairs of eyes, to assist in banking-grade digital onboarding. Often, they know better than machines what to look for, particularly for newly released IDs and older paper IDs, and in terms of new or especially invisible forms of fraud. This is the only route to the highest level of assurance financial institutions (and fintechs) need to truly know their customer is who they say they are.

Trust comes first

Amidst such uncertainty – of our health, the economy, and even our social lives – trust matters most. In the digital world, this is even more true. Customers value signals that their online identities aren’t just being automatically processed, but carefully considered.[…]

read more – copyright by www.forbes.com

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