Car Insurance Portfolio Analysis (Business Intelligence Project)

Overview

This project simulates a real-world insurance portfolio to analyze policy sales, claims patterns, and overall profitability using SQL and Power BI.

Objective

To evaluate:

• Premium revenue
• Claim cost trends
• Loss ratio
• Risk exposure across policy tenures

Dataset

• 1,000,000 simulated policy records (2024)
• Claims data for 2025 and early 2026
• Policy tenure distribution (1–4 years)

Tools Used

• Python (Pandas) – Data simulation
• MySQL – Data analysis
• Power BI – Dashboard visualization

Key Analysis

• Total premium collected
• Monthly claim trends
• Claim-to-premium ratio by tenure
• Risk analysis by policy purchase month
• Future claim liability estimation

Key Insights

• Claims are concentrated on specific purchase dates, indicating clustered risk.
• Longer tenure policies have higher claim exposure.
• Portfolio profitability depends heavily on claim frequency trends.

Dashboard

The Power BI dashboard includes:

• KPI metrics (Premium, Claims, Loss Ratio)
• Monthly claim trend
• Tenure-based profitability analysis

Project Outcome

This project demonstrates how business intelligence techniques can be applied to evaluate insurance portfolio performance and risk exposure.

Dataset

Due to file size limitations, datasets are hosted externally.

Download here:

• Policy Sales & Claims Datasets: https://drive.google.com/drive/folders/1yPwSXpwsKEroSvoZ4YRtTI8-qgkVx4RR?usp=sharing

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