An open database of international sanctions data, persons of interest and politically exposed persons
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Updated
Sep 14, 2026 - Python
An open database of international sanctions data, persons of interest and politically exposed persons
Marble - the real time decision engine for fraud and AML
Money Laundering Detection Using Machine Learning
Connected Data London 2025 Masterclass: Combining Data from Structured and Unstructured Sources to create High-Quality Knowledge Graphs
The source code of the experimental evaluation of Deprez et al. (nd)
In this repo, I trained various models to detect potential money laundering in residential real estate in Bexar County, Texas.
An analysis of the released data on FinCrime Files transactions as depicted on SARs.
This project leverages machine learning models like Random Forest and XGBoost to detect suspicious financial transactions that could be linked to money laundering. Using a dataset provided by IBM, we analyze real-world financial interactions between individuals, businesses, and banks.
Exploring the FinCEN Files Investigation in Neo4j
This project utilize an appropriately characterized banners dependent on ruleset to channel and appropriately distinguish any exchange which falls under Money Laundering.
💰 Forta Bot that detects potential money laundering activity
Real-time fund tracking and fraud detection platform with AI alerts, graph tracing, STR workflows, and banking analytics.
Graph-neural-network fraud detection for UPI payment graphs: catches mule accounts and coordinated fraud rings that per-transaction rules miss. Synthetic benchmark data via SantanderAI/gen-fraud-graph.
Advanced EDA for money mule account detection in banking data. 7.4M transactions, multi-table analysis, behavioral pattern profiling. RBIH x IIT Delhi National Fraud Prevention Challenge Phase 1.
An AI Powered Legal Analyser focusing mainly on AML cases. This uses a front-end built on Google AI Studio and relies on the latest model for reasoning. Results can be downloaded in Excel format.
Open-source blockchain forensics library: transaction graph analysis, address clustering, and explainable AML risk scoring in Python.
Analysis of the "Azerjaibani Laundromat" leaked banking data from OCCRP
Agentic Python pipeline that ingests UK court judgments, extracts POCA 2002 intelligence via Gemini function calling, and surfaces AML conviction patterns by SIC code.
USA-v-McDonalds.org is an official website related to the criminal RICO case targeting McDonald’s Corporation and its subsidiary companies, and their accomplices.
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