Plataforma de CTI Assíncrona focada em Crimes Financeiros (Pix/Cripto) e Compliance Regulatório (Lei 14.790). Powered by LangGraph & AsyncIO.

A deep exploration of how human psychology shapes fraud behavior and how those patterns become measurable signals in transaction data. This article reveals the behavioral, cognitive, and economic forces behind fraud, explaining how ML models detect deviations, anomalies, and intent hidden within financial transactions.

An analysis of the released data on FinCrime Files transactions as depicted on SARs.

Official AMLTRIX Data Exports – Versioned STIX 2.1 bundles, CSVs, XLSX files, and ATT&CK Navigator layers representing the latest AMLTRIX knowledge graph of adversarial behaviors in financial crime. See framework.amltrix.com for methodology and usage.

AFiCATo - Anti Financial Crimes Analysis Tools

Some Deep Learning for Financial Crime Experiments

Financial crime investigation platform that detects suspicious transactions, analyzes transaction networks using graph analytics, and generates Suspicious Activity Reports (SAR) through an interactive investigation dashboard.

Open-source Python toolkit for AML detection and financial crime analytics — transaction graph analysis, anomaly scoring, SAR pattern matching, and SQL helpers for BSA/FinCEN compliance.

Open-source fraud intelligence exchange: 86 threat paths, 141 fraud types, and 36 baselines mapped across 7 frameworks — with STIX 2.1, MISP, TAXII exports and an MCP server for AI-assisted analysis. Detection rules at elchacal801/flame-detections.

White-Collar-Criminals.com official website related to the criminal RICO case targeting McDonald’s Corporation.

Agentic AI Fraud Intelligence Platform with Multi-Agent Collaboration, RAG, Real-Time Risk Scoring, AML/KYC Compliance, Financial Crime Detection and Explainable AI Workflows.

This category delves into the world of criminal activity and justice analytics, using data to uncover hidden patterns and trends in areas such as drug trafficking, money laundering, fraud, cybercrime, and human trafficking.

SQL-based KYC & Risk Profiling Engine simulating bank-style customer risk assessment using rule-based AML logic and FATF-aligned risk indicators

Portfolio of strategy, governance, AI, network intelligence and analytics assets demonstrating the transformation of Financial Crime Operations through graph analytics, risk scoring and artificial intelligence.

JOBGUARD-UK is an automated cyber-intelligence system that actively hunts fake job campaigns across recruitment sites and Telegram. Using a fine-tuned BERT model and network graph analysis, it identifies crypto-mule schemes and organized fraud rings, generating actionable intelligence to disrupt financial crime

Fuzzy matching for sanctions & PEP screening (OFAC list + Onboarding Customers) with Python, Streamlit dashboard - tests.

ASII Strategy — institutional strategy and product intelligence for AI-native Financial Crime Intelligence Infrastructure across UAE & MENA.

Enterprise AML Transaction Monitoring System — 179M transactions, XGBoost AUC 0.9877, SHAP explainability, GenAI SAR generation, Streamlit dashboard, CI/CD

A Claude Skill that adjudicates sanctions / PEP / adverse-media screening hits deterministically. Token-efficient tiered design (parse → cheap FP rules → identifier corroboration → targeted multilingual research). Handles 9+ naming conventions, transliterations, and historical place names.

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.