Detect forged documents using a neural network. That is what this assignment is all about. One of our customers, a large credit provider, now checks all applications manually and is looking for a solution.

Required interest(s)

  • Responsible, explainable, and socially aware data science
  • Human-centered and community-minded information systems
  • Language processing

What do you get

  • A challenging assignment within a practical environment
  • € 1000 compensation, € 500 + lease car or € 600 + living space
  • Professional guidance
  • Courses aimed at your graduation period
  • Support from our academic Research center at your disposal
  • Two vacation days per month

What you will do

  • 65% Research
  • 10% Analyze, design, realize
  • 25% Documentation

This assignment is a question from an Info Support customer. This customer is a large credit provider. The customer daily receives large amounts of documents which are manually checked for modifications and signs of forgery. A example of this is a payslip where the amounts are changed. Automated detection of modifications would contribute to preventing fraud at companies and organizations that process these documents.

Manually checking documents is labor intensive and error prone. Analysing documents with a neural network is potentially cheaper and less error prone. However, we currently do not know to which extent this could replace or support the manual labor. You will work on answering this question.

Research how forged documents can be detected using a neural network. Compare multiple designs and types such as RNN and CNN for this. Create a PoC for one of the designs.

About Info Support Research Center

We anticipate on upcoming and future challenges and ensures our engineers develop cutting-edge solutions based on the latest scientific insights. Our research community proactively tackles emerging technologies. We do this in cooperation with renowned scientists, making sure that research teams are positioned and embedded throughout our organisation and our community, so that their insights are directly applied to our business. We truly believe in sharing knowledge, so we want to do this without any restrictions.

Read more about Info Support Research here.