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3DiVi Blog

Facial Recognition. Three common pitfalls, and how to fix them. Pitfall #2

Key indicators such as recognition accuracy, along with a decrease in operating costs, are becoming the main parameters by which, the effectiveness of face recognition systems is measured.

Mikhaylo Pavlyuk, CCO, 3DiVi Inc. explains what challenges operating experience brings in facial recognition systems. Including those that are not obvious at the start of the project. Let's take a closer look at three of them. Perhaps fixing them can make your processes more efficient, and your business more successful.

Face Recognition Pitfall #2

Lost customers due to the lack of feedback about face image quality during biometric enrolment.


Customer acquisition costs a lot of money. And sometimes the client receives a denial of service due to an uncontrolled environment and the inability to quickly prompt what needs to be changed to obtain the face image with enough quality. Example, we are trying to go through the authorization procedure in a dark room, forgetting to remove the mask. The system is wrong both in matching and liveliness evaluation.

The result is a loss of customer loyalty or loss of a customer.

Estimated Losses

The cost of attracting one new client to the bank for lending services is at least $20. The bank's profit on average from one client is at least $90. In total, each client is $110 in costs and lost profits.


Consider the business case of remote issuance of loans to customers by the Bank. Suppose the Bank issues about 10,000 loans per month using biometric identification. On average, at least 9% of customers try to pass biometric identification in inappropriate conditions. In total, we have about 900 attempts at risk. Assuming that we finally lose 30% of leads, then for the year our lost profit will be more than $ 350,000.


With the help of the quality control algorithm built into the mobile application, we inform the client in about the problems of the environment and the necessary actions on his part, which significantly increases the chance of achieving the desired result.


Increasing profits from transactions related to remote identification by at least 10%.

Go to Face Recognition Pitfall #3 >