Master Thesis Student, Developing AI for monitoring transactional flows

Match My Thesis

Studieprojekt/speciale
Storkøbenhavn

Company description

VP SECURITIES (VP) offers its customers solutions and expertise in the field of securities and investor administration. We have developed internationally recognized securities trading systems and contribute to a stable, safe and well-functioning financial market. VP is the central securities depository (CSD) in Denmark and is approved and licensed by the Danish Financial Supervisory Authority. As a financial infrastructure company, we form an integral part of the financial sector in Denmark.

Project description

VP fokuserer på AI-applikasjoner for å forbedre sine daglige operasjoner ved å overvåke de daglige transaksjonsflyt. The new AI application should monitor the transaction pattern for our customer's settlement flow and notify VP's operations management when typical patterns deviate. Dette er vigtigt for at kunne levere højkvalitets service til markedet, f.eks. Ved at undgå markedsforstyrrelser eller interaktion med en kunde om hvordan man kan modvirke konsekvenserne af uintended adfærd. 

To evalueren AI applicatie mogelijkheden en construct a prototype we zouden verzoeken om analyses te uitvoeren in de volgende stappen:

  • Assess individual customers' historical transaction data, develop pattern and analyze cases when the pattern was broken;
  • Develop an algorithm using machine learning or other data mining techniques to make transaction pattern recognition dynamic to new inputs;

Develop threshold lines when significant divergence from pattern occurs to notify operations management and / or customers;

The research should start with so-called "helicopter" approach looking into AI application possibilities, analyzing possible patterns; Afterward scoping down to specific service improvements and potential up-selling possibilities.

Student description

For this project, we are looking for master students interested in Machine Learning, AI, Big Data, Data Mining, and similar topics. Studenter forventes at have a technical background and be able to create algorithms using machine learning. Erfaring i finanssektoren er et plus, men ikke en nødvendighet. Proficiency in Danish is a plus as well.

Reiskostnader kan være refundert hvis der er en tilstrækkelig afstand til rejse fra universitetet til kontoret i København (Weidekampsgade, 14). Job contract may be considered after a successful cooperation.


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Studieprojekt/speciale
Storkøbenhavn
IT
Maskin & Design
Matematik, Fysik & Nano
Data & analyse
IT - Software



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Nørre Alle 41
2200 København N
Logo: Match My Thesis
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