Johannes Pippidis Lorentzen
About
My primary research focuses on the design, effectiveness, and systemic limitations of financial crime detection systems, particularly anti-money laundering (AML). I combine information security, data science, agent-based modeling, and criminology to investigate how technological, organizational, and institutional constraints influence detection and investigative capabilities.
My broader research interests include artificial intelligence in criminal investigations, criminological theory, Arctic science and safety, and computational modeling of complex systems.
For publications, ongoing research, and additional information, visit my personal academic website: https://pippidis.no
Research
My primary research concerns systems for combating financial crime, with particular emphasis on anti-money laundering (AML), fraud detection, and criminal investigations. I investigate how technological, organizational, and institutional constraints influence the effectiveness of such systems, including challenges related to data availability, observability, analytical capacity, incentive structures, and regulatory requirements.
My research combines information security, data science, software engineering, and criminology. Key methodological approaches include agent-based modeling, simulation, machine learning, network analysis, and the development of formal models for representing and analyzing financial crime. A central objective is to understand not only how these systems can be improved, but also the fundamental limitations affecting their ability to detect criminal activity.
Another major research area concerns the application of artificial intelligence to criminal investigations. This includes automated information extraction from documents, identification of relationships between individuals and events, and methods for detecting missing information and contradictory evidence.
Within criminology, I investigate theoretical and empirical questions relating to surveillance, crime detection, deviant behavior, and the development of foundational criminological models.
I also conduct interdisciplinary research in Arctic science and safety, focusing on measurement technologies, instrumentation, and operational challenges in Arctic environments. My additional research interests include swimming efficiency, international student and researcher mobility, and the simulation of complex systems.
A comprehensive overview of my research areas and publications is available on my personal website: https://pippidis.no
Publications
2026
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Skipanes, Mads Vågane;
Yildirim-Yayilgan, Sule;
Porter, Kyle Andrew;
Jørgensen, Tollef Emil;
Lorentzen, Johannes.
(2026)
Operational Crime Analysis A Computational Framework for the Analysis of Unstructured Textual Data in Criminal Investigations.
Norges teknisk-naturvitenskapelige universitet
Doctoral thesis
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Lorentzen, Johannes Pippidis;
Skipanes, Mads Vågane.
(2026)
Entity recovery in criminal investigations: Evaluating NER and investigator labels on real case texts.
Forensic Science International
Academic article
2025
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Skipanes, Mads Vågane;
Lorentzen, Johannes Pippidis;
Yayilgan, Sule Yildirim.
(2025)
Understanding the role of case management systems in criminal investigations.
International Journal of Law, Crime and Justice
Academic article
-
Lorentzen, Johannes Pippidis.
(2025)
Irregular deposits in Norway: Systemic economic crime in the rental market.
Journal of Economic Criminology
Academic article
2020
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Jullum, Martin;
Løland, Anders;
Huseby, Ragnar Bang;
Ånonsen, Geir;
Lorentzen, Johannes P.
(2020)
Detecting money laundering transactions with machine learning.
Journal of Money Laundering Control
Academic article
2018
-
Jullum, Martin;
Løland, Anders;
Huseby, Ragnar Bang;
Ånonsen, Geir;
Lorentzen, Johannes P.
(2018)
Detecting money laundering transactions -- which transactions should we learn from?.
Norsk Regnesentral
Research report
Journal publications
-
Lorentzen, Johannes Pippidis;
Skipanes, Mads Vågane.
(2026)
Entity recovery in criminal investigations: Evaluating NER and investigator labels on real case texts.
Forensic Science International
Academic article
-
Skipanes, Mads Vågane;
Lorentzen, Johannes Pippidis;
Yayilgan, Sule Yildirim.
(2025)
Understanding the role of case management systems in criminal investigations.
International Journal of Law, Crime and Justice
Academic article
-
Jullum, Martin;
Løland, Anders;
Huseby, Ragnar Bang;
Ånonsen, Geir;
Lorentzen, Johannes P.
(2020)
Detecting money laundering transactions with machine learning.
Journal of Money Laundering Control
Academic article
-
Lorentzen, Johannes Pippidis.
(2025)
Irregular deposits in Norway: Systemic economic crime in the rental market.
Journal of Economic Criminology
Academic article
Report
-
Jullum, Martin;
Løland, Anders;
Huseby, Ragnar Bang;
Ånonsen, Geir;
Lorentzen, Johannes P.
(2018)
Detecting money laundering transactions -- which transactions should we learn from?.
Norsk Regnesentral
Research report
Student thesis or dissertation
-
Skipanes, Mads Vågane;
Yildirim-Yayilgan, Sule;
Porter, Kyle Andrew;
Jørgensen, Tollef Emil;
Lorentzen, Johannes.
(2026)
Operational Crime Analysis A Computational Framework for the Analysis of Unstructured Textual Data in Criminal Investigations.
Norges teknisk-naturvitenskapelige universitet
Doctoral thesis
Outreach
2026
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LectureLorentzen, Johannes. (2026) (anti) Money Laundering. TIØ4317 - Empiriske og kvantitative metoder i finans
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Conference lectureLorentzen, Johannes. (2026) Crypto is just another observability problem. 43rd Cambridge International Symposium on Economic Crime
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Conference lectureLorentzen, Johannes. (2026) Incentive misalignment in AML/CFT compliance. 43rd Cambridge International Symposium on Economic Crime
2025
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Conference lectureLorentzen, Johannes. (2025) The Cyber-Physical Perspective. 42nd Cambridge International Symposium on Economic Crime
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Conference lectureLorentzen, Johannes. (2025) The role of international organizations?. 42nd Cambridge International Symposium on Economic Crime
2024
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Conference lectureLorentzen, Johannes. (2024) How to make it riskier?. 41st Cambridge International Symposium on Economic Crime
2023
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LectureLorentzen, Johannes. (2023) (anti) Money Laundering: From a data science perspective. Guest lecture in machine learning in ACIT4510 Statistical Learning
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Conference lectureLorentzen, Johannes. (2023) How far should banks go?. 40th Cambridge International Symposium on Economic Crime
2022
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LectureLorentzen, Johannes. (2022) (anti) Money Laundering: Gjesteforelesning. Hvitvasking og anti-hvitvasking - gjesteforelesning