The effectiveness of crime prevention and control is under scrutiny owing to limited actionable data and the poor transferability of traditional law-enforcement methods to digital networks. Complexity science enables the development of new tools to map, disrupt, dismantle, or reduce the burden of tackling criminal organizations.
A crime may look like a single event: a fraud, a drug shipment, a cyberattack. But behind it can lie a web of people, resources and connections spanning countries and technologies. To understand where crime comes from – and where it is heading next – means looking beyond individual cases to the systems that connect them.
WHY IT'S COMPLEX
With the most successful offenders leaving few traces, key elements of criminal networks remain hidden; available data largely capture failures, such as arrests, rather than the system as a whole.
At the same time, crime is changing rapidly. Digitalization and globalization are eroding traditional boundaries, creating new opportunities for cybercrime, recruitment and coordination, while technologies such as AI open up entirely new avenues for criminal activity.
These developments are creating new dimensions of criminality that are increasingly difficult to anticipate and counter. Keeping pace requires a deeper understanding of the complex relationships, dependencies and dynamics that shape criminal networks.
OUR APPROACH
Explore the Research Topic ‘Crime in the Digital Age’ – with all publications, stories, projects and visualizations.
Our research provides a systems-level view of crime, with a focus on organized crime and cybercrime. It draws on mathematics, computer science, and psychology, among other fields, and employs agent-based simulations to generate realistic long-run reconstructions, as well as using machine learning to detect behavioral patterns.
Law enforcement must expand its focus from the physical world to the digital realm, where crime is no longer constrained by borders, timelines, or geography – and where case volumes now dwarf the capacity of traditional investigative methods. Cybercrime has shifted from isolated offenses to industrial-scale operations, increasingly accelerated by artificial intelligence, from convincing deepfake impersonations to automated, high-volume cyber fraud. In this environment, approaching incidents one by one makes little sense and drains investigative resources; being able to connect cases instead allows patterns to surface and investigations to move far more efficiently.
By analyzing digital traces, such as blockchain transactions and activity on the dark web, criminal structures can be uncovered. In cooperation with the Bavarian Central Office for the Prosecution of Cybercrime (ZCB), one of Europe’s most successful institutions in this field, numerous high-profile cases have been solved using modern forensic techniques.
Furthermore, with a black box approach (referring to a system with an internal design almost impossible to understand, where the focus is on the system’s outputs), researchers can infer many elements of criminal organizations, allowing them to demonstrate how complexity science can yield insights even from incomplete data. In this context, the effectiveness of crime-control policies can be evaluated; for example, analysis of anti-cartel measures in Mexico indicates that the number of arrests, or even killings, has little impact, so long as cartels can continually recruit new members.
THE IMPACT
By understanding how criminal networks are organized and operate, limited law-enforcement resources can be deployed more efficiently. This helps level the playing field for public institutions against organizations that rapidly adapt their methods, operate across borders, and are often entangled with an economy’s supply chains.
For modern society to endure, rule-of-law institutions are indispensable; accordingly, both ongoing and preventive anti-crime measures must be adapted to incorporate methods from complexity science. Only with these tools can evidence-based policymaking and effective action against criminal organizations be achieved.
