Rate My Professor Finbarr Murphy

Murphy's research focuses on quantitative finance, empirical finance, derivative markets, machine learning applications in finance, and emerging technological risks. He has authored or co-authored over 100 refereed journal papers, edited books, and book chapters, with publications appearing in leading outlets such as Nature Nanotechnology, Small, Transportation Research A to F, and Review of Derivatives Research. Notable recent works include 'A cyber risk prediction model using common vulnerabilities and exposures' (2024, Expert Systems with Applications), 'Are electric vehicles riskier? A comparative study of driving behaviour and insurance claims' (2024, Accident Analysis and Prevention), 'Predictive Modeling for Driver Insurance Premium Calculation Using Advanced Driver Assistance Systems and Contextual Information' (2025, IEEE Transactions on Intelligent Transportation Systems), and 'Bridging transparency in insurance claims prediction: A comparative study of explainable AI and traditional linear models using vehicle telematics data' (2026, Technological Forecasting and Social Change). His research has attracted over €2.8 million in personal funding from EU FP7, H2020 projects, SFI Spokes, and the first Kemmy Business School Principal Investigator-led Marie Skłodowska-Curie Action Individual Fellowship, involving dozens of EU partners. Murphy has influenced policy through presentations to the EU Commission and Parliament's Committee on Legal Affairs, and appointment to the EU expert group on Emerging Risk Liability. Awards include Fulbright Scholar (2012), Erasmus Mundus Exchange Scholar (2014), and Postgraduate Course of the Year Business awards (2011 winner, shortlisted 2012 and 2014).