Fighting crime with graph learning
Organized crime inflicts human suffering on a massive scale: the Mexican drug cartels have murdered 150,000 people since 2006; upward of 700,000 people per year are “exported” in a human-trafficking industry enslaving an estimated 40 million people. These nefarious industries rely on sophisticated m...
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| Format: | Online |
| Sprache: | eng |
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O'Reilly Media, Inc.
2020
Sebastopol, CA O'Reilly Media Inc. |
| Ausgabe: | 1st edition |
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| Online Zugang: | https://learning.oreilly.com/library/view/-/0636920371205/?ar |
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Tag hinzufügen | Zusammenfassung: | Organized crime inflicts human suffering on a massive scale: the Mexican drug cartels have murdered 150,000 people since 2006; upward of 700,000 people per year are “exported” in a human-trafficking industry enslaving an estimated 40 million people. These nefarious industries rely on sophisticated money-laundering schemes to operate. Despite tremendous resources dedicated to anti-money laundering (AML), only a tiny fraction of illicit activity is prevented. The research community can help. Mark Weber (MIT-IBM Watson AI Lab) explores how to map the structural and behavioral dynamics driving the technical challenge, and he reviews AML methods both current and emergent. You’ll get a first look at scalable graph convolutional neural networks for forensic analysis of financial data, which is massive, dense, and dynamic. Mark outlines preliminary experimental results using a large synthetic graph (1M nodes, 9M edges) generated by a data simulator called AMLSim, and he considers opportunities for high performance efficiency, in terms of computation and memory, and shares results from a simple graph compression experiment, all of which supports the working hypothesis that graph deep learning for AML bears great promise in the fight against criminal financial activity. Prerequisite knowledge A basic understanding of data science and graph structures Experience with finance (useful but not required) What you'll learn See why graph deep learning is a powerful tool for finance and other applications This session is from the 2019 O'Reilly Artificial Intelligence Conference in San Jose, CA. |
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| Beschreibung: | 1 Online-Ressource (1 video file, approximately 51 min.) |