🧳 Travel Insurance Claim Classification

This project aims to enhance the accuracy and efficiency of travel insurance claim processing using Machine Learning. Insurance companies often face high volumes of claims influenced by various factors, which can slow down decision-making and increase the risk of errors. Meanwhile, customers expect a fast and reliable claims process.

🎯 Objective

Leverage ML models to predict the likelihood of a claim, enabling:

• ⚡ Faster claim decisions

• ✅ Reduced human error

• 📈 Improved operational efficiency

🧠 Machine Learning Highlights

• Model performance evaluated using ROC Curve

• Applied hyperparameter tuning to optimize model accuracy

• Balanced focus on precision and recall to minimize misclassification

💥 Impact

Implementing ML in this workflow helps:

• Speed up simple claim approvals

• Allow human adjusters to focus on complex cases

• Increase customer satisfaction through responsive and accurate service --

👥 Group Members

Clarissa Beatrice Kosasih

Jeremy Djohar Riyadi

Kelvin Jonathan Yusach

Sherly Vaneza