Cyber Security Insurance Risk Model

Step 1: Select and Train Your Model

Choose your model type and train it with real-world cybersecurity data

Choose Model Type

Neural Network (Standard AI Model)

XGBoost (Better for Business Data)

HuggingFace (Pre-trained Model)

Train Your Risk Assessment Model

Configure and train the AI model using real-world cybersecurity data

Use Real-World Cybersecurity Data

Train the model with actual breach data from public sources

Training Data Size500 companies

Larger sample sizes provide better model accuracy but require more training time

Learning Speed

How quickly the model learns from data. Lower values (0.001) are usually better for accuracy but take longer to train.

Training Rounds

How many times the model reviews all data. More rounds (100+) usually improve accuracy but take longer to train.

Data Chunk Size

How many examples the model looks at before updating. Larger values (32-64) are faster but may be less precise.

Overfitting Prevention

Helps the model generalize better to new data. Higher values (0.2-0.3) prevent the model from memorizing training data.

Troubleshooting Tools

Click "Show Details" to view debugging information