Health Insurance Premium Prediction
This project develops a machine learning model to predict health insurance premiums based on applicant information such as age, smoking habits, BMI, income, and medical history. The model is deployed in a Streamlit application so that underwriters and decision-makers can generate premium estimates quickly and consistently.
Project Overview
Health insurance pricing needs to be accurate and fair. Predicting premiums helps companies:
- Ensure fair pricing for customers
- Reduce risk for the company
- Speed up the underwriting process
By training a machine learning model, underwriters can:
- Approve low-risk applicants quickly
- Flag high-risk applicants for further review
- Standardize pricing decisions
The Streamlit app makes it possible to access predictions instantly through a simple web interface.
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