Zsolt has over 10 years of experience in credit & fraud risk analytics and modeling in Europe and the US. Currently he is working in Citi’s Global Fraud Analytics Oversight Team leading analytics oversight for North America. He is located in New York, USA, has been in his current role for over 5 years. Beside analytics oversight he has focused on analytics proof of concepts in Machine Learning for fraud detection and fraud risk appetite quantification. Prior to his current role he worked as a data scientist for a credit management company in the UK and in credit / fraud analytics for Citi in Hungary. His current area of interest is adoption of anomaly detection and machine learning algorithms for fraud detection. He holds an MSc in Quantitative Economics from the Corvinus University of Budapest.