Assisted Image Capture (AIC) helps to avoid some of the most common mistakes that people make when going through verification flow, especially when doing it for the first time. Examples include taking low-quality photos or failing to show both sides of the ID. Assisted Image Capture provides real-time user feedback in the moment, within the verification flow itself, to avoid the need for resubmissions and correct errors prior to user submission.
According to Janer Gorohov, Veriff co-founder and COO, after analyzing millions of verifications the company recognized that people tend to make the same mistakes when going through the identity verification process. “As delays cost time and money for our clients, we created a solution that gives end-users real-time feedback and helps honest people get through IDV so they can start using the vendor’s services. As AIC has been a part of our product for a while now and the results have been superb, we identified that making it a standalone product could help many companies facing similar challenges.”
Assisted Image Capture use cases range from sharing economies to fintechs, marketplaces and beyond. It has provided an increase in first-time pass rates and general operational stability as well as decreased general and verification-related costs.
Veriff’s verification technology uses machine learning to prevalidate sessions before they are reviewed (if necessary). Veriff detects errors in photos that would make them unsuitable and communicates the right fixes to users in real-time. Blurriness, glare or an obscured face or damaged/unusable ID documents are just a few examples of common mistakes.
Assisted Image Capture has significantly boosted user conversions and decision speed for various Veriff partners, who report fewer rejections and failed attempts and significant improvements both in terms of customer experience as well as operational scalability.
