34 results for “topic:transaction-monitoring”
Open source AML and Fraud Detection using Machine Learning for Real-Time Transaction Monitoring
Welcome to an open-source transaction monitoring engine! This product is designed to simplify the definition and management of business rules while also offering a scalable infrastructure for rule execution and backtesting.
Blnk Watch is a domain-specific language (DSL) for creating real-time transaction monitoring rules. It enables you to define conditions and automated actions for detecting fraud, enforcing limits, and staying compliant. A Watch script is declarative: you describe what to detect and what action to take—the engine handles evaluation at runtime.
Name Matching ML model for entity resolution and transaction monitoring
⚡ Real-time fraud & anomaly detection system for streaming transactions. Built with Kafka Streams + Isolation Forest ML. Low-latency processing, online learning, and scalable architecture for detecting fraud patterns in transaction data. 🚨🔍
End-to-end KYC/AML compliance data analysis using mock datasets. Includes customer risk scoring, suspicious transaction flagging, and compliance reporting in Python (Pandas, Matplotlib).
Full-stack digital payments compliance engine—UPI/RTGS simulator, AML rule engine, ML-based STR detection, SHAP explainability, and audit-ready dashboards.
This project is a cryptocurrency automation tool designed to interact with blockchain data and exchanges for analytical and operational purposes. The bot helps automate routine tasks, monitor transactions, and process market-related information in real time.
An AI-powered fraud detection system that uses machine learning to detect suspicious financial transactions in real time. Features include interactive dashboards, secure authentication, and comprehensive reporting for fintech risk analysis.
False-Positive Reduction Lab : rule-based transaction monitoring with threshold tuning and cost trade-offs. Demonstrates how adjusting detection rules reduces noise, lowers investigation cost, and improves fraud catch.
A simple CLI tool to monitor and log Solana wallet payment transactions in real-time
Enterprise-grade fraud & AML detection with ML and deep learning (XGBoost, LightGBM, Autoencoder, LSTM, Transformer). Real-time API, explainability (SHAP), BI export, Streamlit dashboard. PaySim-compatible.
SQL-based AML transaction monitoring engine simulating rule-based detection and alert generation.
Track large USDT movements on Ethereum automatically and react fast to suspicious activity. This n8n workflow automation monitors on-chain transfers, logs high-value transactions in Airtable and sends real-time Slack alerts. A focused n8n workflow template for crypto monitoring, compliance checks and treasury visibility.
Synthetic Economic Crime monitoring lab. Transaction monitoring, alert explainability, weekly MI, Streamlit dashboard.
High-throughput transaction event ingestion with Google CEL rule evaluation | Quarkus 3.x + Vert.x Event Bus + Java 21 Virtual Threads
Production-grade backend for internal crypto transaction monitoring, deterministic risk scoring, compliance workflows, and immutable audit logging - inspired by real exchange AML systems.
Real-time fraud detection with explainable AI - handles imbalanced data (0.17% fraud) using SMOTE + Random Forest. Streamlit dashboard with SHAP explanations shows why each transaction is flagged.
ML model developed using European credit card transaction data to identify suspicious activities.
Analyse alert-to-SAR conversion rates and recommend threshold adjustments for transaction monitoring rule engines.
A full-stack fintech case resolution system with multi-agent automation for fraud detection, dispute management, and automated actions with explainable traces and observability.
Transaction monitoring that deploys in 60 seconds.
High-performance blockchain monitoring service supporting Ethereum, BSC, and Bitcoin with real-time wallet tracking and multi-chain architecture
Practical repository for transaction monitoring scenarios, red flags, suspicious activity indicators, and AML-focused analytical review.
KYT compliance template platform — alert severity matrix, indirect exposure modelling, VASP taxonomy. Built on 4 years of VASP transaction monitoring work.
Professional toolkit for crypto investigations, AML/CTF intelligence, blockchain risk analysis, and compliance research.
Real-Time Insights into Transaction Activity with Scalable Streaming and Analysis.
Portfolio Project: AI-driven financial transaction risk detection using automation workflows and real-time model scoring.
Real-time Solana wallet transaction monitor built with Rust — fetches SOL/SPL transfers, exports CSV, dark-theme analytics dashboard
Rules based KYC Risk Scoring Dashboard -SQL and PowerBI. Automates customer classification into Low/Medium/High risk tiers using onboarding data.