Data Analysis Project Using Power Bi Insurance Risk Claims Analysis l Analysis Dashboard
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Step 1: Data Collection and Preparation
Collect insurance claims data, covering fields like policy details, customer info, claim amounts, claim type/status, and other relevant metrics.
Clean and transform the data using Power Query, create necessary calculated columns (such as age groups, active/inactive policy status), and profile the dataset for quality and completeness.
Step 2: Import and Model Data
Load data into Power BI from a data source (SQL Server, CSV, Excel, etc.).
Model the relationships between tables—link claims to policyholders, policies, and claim types.
Step 3: Create DAX Measures
Define measures using DAX for essential KPIs, such as total claims, claim frequency, average claim amount, high-risk policyholder percentage, claim rate, and average premium.
Calculate risk scores or fraud likelihood by analysing patterns across multiple attributes (e.g., claim amount, agent behaviour, frequency).
Step 4: Design Visualizations
Add interactive report elements:
Cards for KPIs (total claims, claim amounts, premium collected, etc.)
Bar and ribbon charts for claim status, policy types, age groups
Line/area charts for trends over time (claim frequency, settlement times)
Donut/pie charts for policy status breakdown
Slicers for filtering by customer, region, agent, or policy type.
Optimize layout and colour palette to ensure clarity and readability. Apply a consistent theme across visuals for a professional appearance.
Step 5: Fraud and Risk Insights
Use Power BI analytics to identify possible fraudulent claims by visualizing anomalies, claim patterns, and outliers in the data.
Incorporate risk scoring using DAX and conditional logic to highlight high-risk policyholders or claims.
Step 6: Dashboard Deployment and Sharing
Publish the report to Power BI Service, set up a workspace, and pin key visuals to form an actionable dashboard.
Apply Row-Level Security as needed for client or agent-specific views.
Schedule data refreshes for real-time insights and maintain continuous reporting.
Step 7: Actionable Insights
Monitor claims in real time, detect workflow bottlenecks, and forecast trends for operational planning.
Use the dashboard to improve customer communication, transparency, and claims management efficiency.
By following these structured steps, you can build a robust insurance risk and claims analysis project in Power BI, enabling data-driven decision-making for insurers, agents, and management.
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Data Set link : https://docs.google.com/spreadsheets/...
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