Success Story - en

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.

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.
Computer Vision Engineering Division