Anomaly Detection using Deep SVDD
Anomaly detection has numerous applications in a wide variety of fields. In banking, with ever growing heterogeneity and complexity, it is difficult to discover deviating cases using traditional investigation techniques and pre-defined scenario searches. In this talk we’ll have a walk-through on how Swedbank’s deep learning models run on a state-of-the-art platform can help to detect unseen anomalies and deviations utilizing a large spectrum of features.
Mehrdad Mamaghani holds a PhD in applied mathematical statistics from Stockholm University along with 10+ publications. Previously, Mehrdad has worked within the pharmaceutical and communication industries. At Swedbank, along with rest of the Analytics & AI group, Mehrdad and his colleagues conduct extensive work and research to better leverage the data within the bank as well as creating frameworks for more efficient and customer-oriented banking processes using deep learning techniques and advanced hardware platforms.