Anomaly Detection in transactions volumes

The objective of the project is to investigate how machine learning techniques can be used to detect anomalies in volumes of transactions. This requires the student to conduct a literature review about the topic as well as experimenting with a subset of selected machine learning techniques. The results from the research could help the partner organization in improving in place mechanisms used to detect anomalies in volume of transactions.

Faculty Supervisor:

Anthony Bonner

Student:

Hervé Vincent Dukuze

Partner:

Ethoca Technologies

Discipline:

Computer science

Sector:

Information and communications technologies

University:

University of Toronto

Program:

Accelerate

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