During the 6-month thesis internship, you will be involved in the research and development of an entity-matching algorithm that uses Entity Linking to match transactions and sanctioned entities. You will explore how to use the context and information inside the transaction and the sanctioned entities to generate and rank possible matches. You will also evaluate the performance and impact of the algorithm on the sanctions detection models and propose improvements or enhancements. By working on this project, you will gain valuable experience and skills in the field of sanctions detection and Entity Linking.

This project is aimed at creating new logic to detect transactions that benefit sanctioned entities, which are individuals or organizations that are subject to government-imposed restrictions. Sanctioned entities may use various techniques to evade detection, such as omitting relevant information from transactions, or using aliases or front companies. To also detect those transactions, we challenge you to leverage the context and information in transactions, as well as that of the sanctioned entities to match them accurately. The project idea is to design and implement an entity-matching algorithm that uses Entity Linking, a technique that generates and ranks possible entities based on their similarity and relevance. By using Entity Linking, we hope to improve the accuracy and efficiency of our transaction filtering system and contribute to the fight against financial economic crime.

The tools that are use:

• Python to perform analyses data and create models

• Databricks to gather and transform data

• Word/PowerPoint/Excel

In Rabobank we appreciate variety and how different backgrounds, and thinking could challenge us to deliver the best product. The team construct reflects this and consists of people with different cultural backgrounds. We are a team who can appreciate ‘gezelligheid’ during lunch and know how to laugh.

• Last year Master student in a quantitative field, such as computer science, econometrics, or artificial intelligence.

• Average grade above 7.5

• Comfortable with programming using Python

• You’re fluent in English

• Independent worker: you'll need to take initiative, ask questions when necessary, and manage your own time effectively. You're expected to find your own university assignment and meet agreed-upon deliverables.

Apart from the satisfaction of completing a leading industry question and gaining insight into a global bank, we will also:

• Remunerate you € 600.00 a month based on 36 hours per week

• Reimburse your travel expenses to and from work (conditions apply) if these are not covered by your student public transport product

• Supervision from the team

• For questions about the internship and the team reach out to Koen Hoogkamp at Koen.Hoogkamp@rabobank.nl.
• For questions about the recruitment process and working at Rabobank reach out to Michelle Veeke at Michelle.Veeke@Rabobank.nl.

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