Cross-border forensic profiling of fraudulent identity and travel documents: A pilot project between France and Switzerland
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The serial character of document fraud and its connection to organised crime groups who produce, sell and/or use fraudulent documents is a challenge for security and crime fighting. As a response, the added value of forensic intelligence is increasingly recognised. Using a forensic profiling method and a dedicated system deployed in Switzerland, document examiners can detect series (i.e., documents that share a common source) of fraudulent documents conveniently and efficiently. This detection can trigger or orientate investigations, supports crime intelligence efforts, and facilitates cross-jurisdictional cooperation. This study aims to assess the suitability of the forensic profiling system for international purpose and the efficiency of the method to detect cross-border series. The forensic profiling system has been deployed in France in the framework of a cross-border pilot project conducted by the School of Criminal Justice from the University of Lausanne and the French National Police (Division Nationale de Lutte contre la Fraude Documentaire et à l'Identité) over the period July 2019-May 2020. Data from the Swiss and French forensic profiling systems were compared to each other to detect cross-border series. The study sought to create operating conditions as close as possible to the real-life conditions of the profiling systems. The results are extremely positive both quantitatively and qualitatively. They demonstrate the benefit of setting up a systematic exchange of forensic data issued from profiling systems for fraudulent identity documents between France and Switzerland, let alone between any other countries. The results open up a very promising prospect for a sustained operational implementation by the police services of both countries and the extension of the exchanges internationally.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it