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Anti-Money Laundering Early Warning System Based on Deep Learning/.DS_Store
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Intelligent Anti-Money Laundering Behavior Monitoring Platform/.DS_Store
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Machine Learning-Driven Anti-Money Laundering Investigation Assistant Software/.DS_Store
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# AML-Monitoring-Engine | ||
AML end to end system | ||
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## General Information | ||
- **Full Software Name**: Intelligent Financial Transaction Anti-Money Laundering Identification Tool Platform | ||
- **Version**: V1.0 | ||
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## Development Environment | ||
- **Development Hardware Environment**: | ||
- CPU: Intel(R) Core(TM) i5-4200H, 2.8GHz | ||
- RAM: 8GB | ||
- Hard Drive: 1TB | ||
- **Development Operating System**: Windows 11 Enterprise Edition | ||
- **Development Tools**: IntelliJ IDEA V2023 | ||
- **Programming Language**: Java | ||
- **Source Code Size**: 25,466 lines | ||
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## Runtime Environment | ||
- **Hardware Requirements**: | ||
- Quad-core CPU | ||
- 8GB RAM | ||
- Integrated Graphics | ||
- Gigabit Network | ||
- SSD with 500GB or more | ||
- **Operating System**: Anolis OS | ||
- **Supporting Software**: | ||
- JDK 9 or above | ||
- MySQL 8.0 | ||
- Apache Tomcat | ||
- Redis | ||
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## Purpose of Development | ||
The primary goal is to enhance the efficiency of anti-money laundering (AML) efforts in financial transactions, reduce risks, and ensure the security of funds. | ||
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## Target Domain/Industry | ||
- **Domain**: Financial Technology (FinTech) | ||
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## Key Features | ||
1. **Real-Time Monitoring**: | ||
Utilizes big data, machine learning, and artificial intelligence to analyze large volumes of financial transaction data in real-time. | ||
2. **Suspicious Pattern Detection**: | ||
Automatically identifies unusual patterns, such as large fund transfers or frequent cross-border transactions. | ||
3. **Model Optimization**: | ||
Continuously improves detection accuracy using deep learning algorithms. | ||
4. **Risk Alert Mechanism**: | ||
Initiates investigation procedures immediately upon detecting potential money laundering activities. | ||
5. **Data Integration and Sharing**: | ||
Enables cross-bank and cross-border data sharing to strengthen institutional collaboration. | ||
6. **Compliance Support**: | ||
Provides compliance reports and audit tools to meet international AML standards. | ||
7. **Efficiency Improvement**: | ||
Enhances precision and effectiveness of AML processes to prevent financial crimes and ensure system stability. | ||
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## Technical Characteristics | ||
- **Type**: Big Data Software | ||
- **Key Features**: | ||
- Employs AI deep learning and big data analysis for real-time monitoring of financial transactions. | ||
- Supports anomaly detection and risk level evaluation. | ||
- Facilitates multi-dimensional data integration and automated workflows to improve risk control efficiency. | ||
- Offers visualized reports for clear understanding of risk scenarios, enabling precise and efficient risk management. | ||
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## Software Classification | ||
- **Category**: Application Software |