Facial Recognition AI — The Missing Security Link in Mobile Payment Apps

Hemant Warier
Published in
4 min readAug 17, 2020


A user making payment through mobile payment app
Image by Markus Winkler from Pixabay

Over the years, there has been a great increase in digital payments in India and the rest of the world. People use different mobile payment apps for eg., Alipay, WeChat, Apple Pay, PayPal, Samsung Pay, Amazon Pay, Google Pay, etc., to send money to other people or businesses. According to BusinessWire, The transaction value of global mobile payments market was USD 3714.5 billion in 2019. It is expected to reach a value of USD 12,407.5 billion by 2025, registering a CAGR of 23.8% over the forecast period 2020–2025.”

The statistics posted by Merchant Savvy on their website show that 1 Billion people are predicted to use a mobile payment app worldwide in 2020.


Most of the mobile payment apps use Single Factor Authentication (1FA) or Two Factor Authentication (2FA) for verification of users during sign up and even for making payments. The most common authentication factors used by mobile payment apps are

  • OTPs via email or SMS.
  • Mobile screen locks like pin, password, pattern, or biometric fingerprints.

Usage of mobile screen locks like a pin, pattern, password & biometric fingerprints is still considered to be safe. But OTPs via SMS are prone to hacks by SIM jacking.

According to NortonLifeLock, “A SIM jacking is a fraud that occurs when scammers take advantage of a weakness in two-factor authentication and verification in which the second step is a text message (SMS) or call to your mobile phone number.”


To ensure absolute security, Mobile payment apps need to use multiple-MFA-authentication factors for verification of users & even while making payments via these apps. This will ensure that there is an extra layer of security added to make the payments secure and will curb losses for the customers. This will also increase the customer retention rate for the mobile payment apps as customers will also feel very secure using an app that uses multiple-MFA-authentication factors. Using this, OTPs or screen lock can be complemented with other authentication factors to make the apps more immune to frauds.

Given today’s technology, the secure & optimal authentication factor which can be used to authenticate transactions is AI-enabled facial recognition. Facial recognition is currently one of the fastest-growing biometric technologies which are powered by AI. Over the years, the accuracy of facial recognition technology has increased with the help of deep learning.


FaceQuest provides advanced, ethical facial recognition services to students, developers, and businesses worldwide. FaceQuest’s facial recognition app is powered by deep learning, which helps it to match & verify photos. The innovative API platform lets developers & businesses add state-of-the-art facial recognition capabilities into their own software.

FaceQuest’s face match can verify if any two photos belong to the same person or not. This can help the mobile payment apps industry in two ways:

  1. New User Signup — As the first step, the user can be asked to upload a selfie to the app during the signup process. The uploaded photograph can be stored as a reference image of the user. For those mobile payment apps, which also do KYC by asking users to upload pictures of their ID cards during signup, the user’s selfie photograph can be matched with the ID card pictures & be verified for accuracy.
  2. Authentication of Payments — While making payments, the app can take a photograph of the user and the user’s current photograph can be matched with the reference image that was stored during the signup process. This will make sure, no one else but the registered user is making payments through the app.

FaceQuest offers both storage & non-storage solutions to business.

FaceQuest offers AI facial recognition tool. It can be used by mobile payment app companies & can be integrated via APIs
FaceQuest’s Face Verification Dashboard
  1. In storage solution, the mobile payment app companies can store the reference images of the user in the FaceQuest’s encrypted server, and whenever the user makes a payment, the mobile payment app can send the photograph to the FaceQuest server to match & verify it with the reference image using the face verification tool.
  2. In the non-storage solution, each time a user wants to make the payment, the business can send both the reference image & the current photograph of the user to FaceQuest server via API and get the verification result in a matter of seconds.

Signup for a 7 day free trial of FaceQuest’s facial recognition service.



Hemant Warier
Editor for

Sales & Marketing at notesally.com || Ex-Uber