Identity Recognition

Description: a quick and convenient credit check for the customer when issuing a Bank loan involves recognizing their personal documents for identification. At the same time, risk reduction is ensured by high-quality cross-checking of documents by operators. Automation of this process in order to reduce the cost of the contact centre can be obtained by using modern image recognition methods.

Context: need to build an alternative model of recognition, to spend fewer resources on manual review of the documents.

Decision: a model for recognizing key document fields is built.

Results:
The solution is integrated into the customer's business process:

Reduced staff costs 10 %;
Improving the quality of risk analysis by 15 %;
Increase the speed of application approval by 30 %.

Also, pilot tests were conducted on the following documents:

Passport;
SNILS;
Driver's license;
Passport of the vehicle.

To build the model, we used:

Set of images and scans of personal documents;
Marking up images with text boxes;
The true value of each field;
Database of named entities in the Russian Federation.

Simulation result:

Model for recognizing the main elements of the passport;
Model of character recognition for each element of the passport.

Customer: Finance, Banking, Insurance

Technology stack: OCR, TensorFlow, Python.