Zain The AnalystAvailableCase Study
Data Analysis and Visualization
Insurance Claims Analysis Dashboard
A Power BI dashboard that helps understand claim amounts, customer groups, vehicle patterns, and financial trends.
Key Metrics Analyzed
Total Claim Amount$1.88bn
Total Customers38K
Average Claim Frequency0.51
Claim Frequency19K
Maximum Claim Amount$100K
Average Household Income$147K
Private Insurance80%
Commercial Insurance20%
Overview & Objectives
This project analyzes car insurance claim data using Power BI. It includes demographic analysis, insurance claim analysis, and financial analysis. The dashboard helps users quickly understand which customer groups, car models, car makers, income groups, and age groups are linked with higher claim amounts.
The dashboard includes three report pages: demographic analysis, insurance and claim analysis, and financial analysis. It uses interactive filters, KPI cards, bar charts, donut charts, pie charts, and line charts to make the insurance data easy to explore.
Project Goal
Build a clear Power BI dashboard that helps users explore insurance claims and understand the main reasons behind claim amounts.
The Business Problem
The insurance claim data had many different customer and vehicle details, but it was not easy to understand the main patterns. The business needed one clear dashboard to compare claims by gender, age, marital status, education, income, car maker, car model, and insurance type.
Methodology
My Approach
- 1I cleaned and prepared the insurance data.
- 2I created useful measures in Power BI.
- 3I designed three dashboard pages for demographic, claim, and financial analysis.
- 4I added filters so users can explore the data by customer and vehicle details.
Implementation
Roadmap Execution
Data Preparation
Cleaned and prepared the insurance claims data.
Data Modeling
Created the Power BI data model and connected the main fields.
DAX Development
Built measures for claim amount, claim frequency, income, and customer totals.
Dashboard Design
Designed demographic, insurance claim, and financial analysis pages.
Interactive Filters
Added slicers for gender, marital status, car model, car maker, age group, income range, and coverage zone.
Visual Formatting
Formatted charts and KPI cards so business users can read the dashboard easily.
Key Features
Demographic analysis page
Insurance and claim analysis page
Financial analysis page
Interactive filters
KPI cards
Claim amount by gender, parents, age group, marital status, and education
Claim amount by car model and car maker
Income distribution and coverage zone analysis
Business Impact
Helps identify customer groups with higher claim amounts
Makes insurance claim trends easier to understand
Supports faster business decisions
Shows vehicle and financial factors linked to claims
Reduces manual analysis work
Challenges Overcome
- Combining customer, vehicle, and financial data into one dashboard
- Making claim patterns easy to understand
- Designing clear filters for different user questions
- Showing large claim values in a simple format
Outcomes
Final Outcomes & Learnings
- The final dashboard gives a clear view of total claim amount, claim frequency, customer count, income patterns, insurance type, car model performance, and demographic claim trends.
- Users can quickly compare claim patterns across customer groups, vehicles, and financial segments.
Project Gallery & Screenshots
Technologies Used
Power BIPower QueryDAXExcel
Data Sources
Car insurance claims datasetCustomer demographic dataVehicle dataFinancial data
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