When Tony Fitzgibbon launched Data Zoo a decade ago, data had begun to transform the world. It was in 2006 that British mathematician Clive Humby declared that “data is the new oil”, and by 2013 the regulatory landscape and risks surrounding data was evolving rapidly.
Mr Fitzgibbon, an accountant turned entrepreneur, saw a need to create a global digital identity solution that would give people around the world confidence in how organisations deal with their data.
This came with a recognition that existing digital businesses would collapse if they continue down the path of a centralised approach to managing customer data.
So Mr Fitzgibbon launched Data Zoo, a modern way to verify customers with a single, global integration into an ecosystem that allows clients to streamline the deployment of identification verification.
Data Zoo’s core product is IDUX, a digital identity ecosystem for businesses to build mutual trust with their clients. The company was listed as one of the fastest growing tech companies in Australia by Deloitte in 2021 and 2022.
The company’s product combines identity verification expertise with accredited reusable digital identity credentials and data sharing consent management.
The company is headquartered in Sydney, and now has offices in New York, Amsterdam, New Zealand, Singapore and the Philippines.
Data Zoo’s offering of identity proofing, fraud detection and user authentication tool gives organisations the ability to apply selective and intelligent friction that matches the level of risk involved in the situation, adopting privacy-by-design principles at its foundation.
At the end of 2021, the company obtained an Australian Open Banking licence through a Consumer Data Right accreditation. This means it can now leverage the vast potential of banking data in its offering.
Data Zoo is also looking to incorporate cutting-edge technologies. It has now implemented advanced biometric authentication techniques including facial and voice recognition, to verify the identities of users more accurately and securely.
It is also using machine learning algorithms to analyse the huge amounts of data going through its systems and to detect potentially fraudulent behaviour.
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