IDfy has introduced a two-click onboarding platform, the simplest onboarding initiation. It starts with just two pictures from the individual – a photo of the ID and a selfie.
In the back end, our Extraction and Verification Engine (EVE) has APIs that detect tampering in cards, extract information from digital images, accurately match the selfie to the card, and establish that it’s a live selfie. All this in 5 seconds.
EVE’s machine learnt models detect tampering on ID cards, extract relevant information from digital documents, run API-led realtime checks across public data sources, and use advanced ML algorithms to compare the selfie to the card, and also determine if the selfie is a live selfie.
On IDfy’s immediate future, Ashok listed what he sees as the 3 key growth drivers for the company.
- Deeper fraud detection: Creating more fraud detection capabilities that allow us to detect new-age and emerging fraud as well as fraud that previously went undetected.
- Expanding fraud detection use cases: Continuously expanding use cases of fraud and encompassing specific requirements of industries such as Telecom, Sharing Economy, and P2P transactions.
- International Expansion: Expanding to emerging economies with similar characteristics and complexities as India for availability and accessibility of individual data.