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BERT Regulatory Text Classification 01

Developed by yirifiai1
BERT-based multi-label classification model for financial regulatory domains, optimized for anti-money laundering/counter-terrorism financing regulatory texts
Downloads 28
Release Time : 6/6/2024

Model Overview

This model is a financial regulatory-specific model fine-tuned from ProsusAI/finbert, excelling at multi-label classification tasks, particularly suitable for financial institution compliance text analysis

Model Features

Financial domain specialization
Fine-tuned from the financial domain pre-trained model finbert for better understanding of regulatory terminology
Multi-label classification capability
Can simultaneously identify multiple related regulatory categories in text
High-precision risk identification
Achieves F1 score of 0.8637 on financial regulatory texts, accurately identifying risk-related expressions

Model Capabilities

Financial text classification
Regulatory compliance analysis
Risk factor identification
Multi-label prediction

Use Cases

Financial compliance
Anti-money laundering text screening
Automatically identifies money laundering risk signals in transaction reports
High-accuracy identification with F1 score of 0.8637
Regulatory policy classification
Performs multi-dimensional classification labeling on financial regulatory policy documents
Risk management
Risk factor extraction
Extracts various risk-related expressions from financial institution reports
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