Detecting Fraud in Company Data Sources
05.06.2023Modern companies record large amounts of data regarding their daily workflow. While professional auditors regularly screen this data to find fraudulent abuse of company assets, the size of tracked data in companies is continously increasing. This makes automated fraud detection through artificial intelligence a promising research topic.
This work focuses on how well machine learning approaches can detect fraud in company data. Tasks can range from applying machine learning to different views on the company workflow, to evaluating the use of different types of machine learning approaches.
Supervisor: Julian Tritscher
