Hello everyone, I’m Ankit, and welcome to this complete Power BI Insurance Dashboard Tutorial. In this project, we’ll build a professional insurance analytics dashboard from scratch using a realistic sample dataset. You’ll learn how to import data, clean and transform it with Power Query, create relationships, write powerful DAX measures, and design interactive KPI cards, charts, gauges, and slicers. We’ll analyze policy performance, premium collection, claims, customer retention, renewal rates, underwriting metrics, and policyholder demographics. Whether you’re a beginner, preparing for interviews, or building your Power BI portfolio, this hands-on project will help you gain practical Business Intelligence skills that are highly valued in today’s data analytics industry.

Here is the dataset used in the project: https://www.kaggle.com/datasets/slidescope/slidescopes-insurance-analysis-and-kpi-dataset

What We Are Building in This Power BI Insurance Dashboard

Before we start creating visuals, writing DAX measures, or designing the report layout, let’s first understand what this dashboard is designed to achieve. Every successful Power BI project begins with a clear understanding of the business requirements, and this Insurance Dashboard is no exception. Instead of displaying raw policy records, our objective is to transform insurance data into meaningful business insights that decision-makers can use every day.

In this project, we will build a fully interactive Insurance Dashboard that provides a complete overview of policy sales, premium collection, claim performance, customer satisfaction, renewal trends, and profitability. The dashboard has been designed with a clean executive-style layout, making it suitable for insurance companies, analysts, business managers, and anyone looking to build an impressive Power BI portfolio project.

At the very top of the dashboard, you will notice three slicers that allow users to filter the report dynamically. These include Policy Type, Sales Channel, and Claim Status. By selecting different combinations of these filters, every visual on the dashboard updates automatically, allowing users to analyze specific segments of their insurance business. This interactive filtering capability is one of the strongest features of Power BI and makes dashboards far more valuable than static reports.

On the left side of the dashboard, we have several KPI Cards that summarize the most important business metrics. These cards provide executives with an instant overview of overall business performance without requiring them to examine detailed reports.

The KPIs included in this dashboard are:

• Policies Sold
• Total Premium
• Total Assured Amount
• Claim Processing Time

These metrics answer some of the most common business questions, such as:

• How many policies have been sold?
• What is the total premium collected?
• What is the total insured value?
• How efficiently are claims being processed?

Immediately next to these KPI cards, we have a series of Gauge Charts that measure customer and policy performance. Gauge visuals are excellent for comparing actual performance against a predefined target.

The dashboard includes the following gauges:

• Policy Renewal Rate
• Net Promoter Score (NPS)
• Customer Retention Rate
• Policy Lapse Rate

These KPIs provide valuable insights into customer loyalty and overall business health. For example, a high renewal rate indicates satisfied customers who continue their policies, while a lower lapse rate reflects stronger customer retention strategies. Similarly, the Net Promoter Score helps measure customer satisfaction and their willingness to recommend the insurance company to others.

In the center of the dashboard, we have one of the most informative visuals—the Insurance Performance Matrix. This matrix compares each policy category across several important insurance performance indicators.

The policy types included in this project are:

• Disability
• Health
• Home
• Life
• Travel

For every policy type, we will display metrics such as:

• Claim Settlement Ratio
• Underwriting Loss Ratio
• Combined Ratio

These measures help evaluate how efficiently claims are settled, whether underwriting operations remain profitable, and how well each insurance product performs financially. Insurance companies frequently monitor these metrics to identify areas requiring operational improvement or pricing adjustments.

On the right-hand side of the dashboard, we have a Clustered Column Chart comparing Profit versus Expenses by Policy Type. This visual allows users to quickly identify which insurance products generate the highest profits and which incur higher operational costs. Comparing profits and expenses side by side makes it much easier to evaluate overall business profitability and identify opportunities for cost optimization.

Below the performance matrix, we have another important visualization titled Annual Premium Equivalent (APE) Performance by Sales Channel. This chart compares the premium generated through different sales channels, including:

• Agents
• Bancassurance
• Brokers

This analysis helps insurance companies determine which distribution channel contributes the highest premium revenue and supports better sales planning and resource allocation.

Finally, on the bottom-right side of the dashboard, we have a Policy Holder Age Distribution donut chart. Customer demographics play a significant role in insurance analysis, and this visual helps us understand which age groups represent the largest share of policyholders.

The dashboard categorizes customers into age groups such as:

• 30–35
• 35–40
• 45–50
• 50–55
• 55–60

Understanding customer age distribution enables insurers to develop targeted marketing campaigns, design age-specific insurance products, and improve customer acquisition strategies.

Throughout this tutorial, we will build each of these visuals step by step. We will begin by importing the dataset, cleaning and transforming the data using Power Query, creating relationships where necessary, developing DAX measures for KPIs and calculations, and finally designing a professional, interactive dashboard that closely resembles real-world insurance business reports. By the end of this project, you will have not only learned valuable Power BI techniques but also created a portfolio-ready dashboard that demonstrates practical Business Intelligence and data visualization skills.

Step-by-Step Guide to Building this Power BI Insurance Dashboard

Now that we understand the dataset and the business requirements, it’s time to build the dashboard from scratch. Throughout this tutorial, we’ll follow the same workflow used by professional Power BI developers—starting with importing the data, creating the required visuals, formatting them professionally, and finally adding interactivity through slicers. By following these steps, you’ll not only recreate this dashboard but also gain practical experience that you can apply to your own Power BI projects.

Step 1: Import the Insurance Dataset

Open Power BI Desktop and click Get Data from the Home ribbon. Since our sample data is stored in an Excel workbook, choose Excel Workbook, browse to the dataset file, and click Open. Select the worksheet containing the insurance records and then click Load.

If your data requires cleaning, choose Transform Data instead of Load to open Power Query. Here you can remove blank rows, correct data types, rename columns, and ensure fields like Premium Amount, Assured Amount, and Claim Amount are stored as numeric values. Once everything looks correct, click Close & Apply.

Step 2: Review the Data Model

After importing the dataset, switch to the Model View. Since this project uses a single table, no relationships are required. However, if your data is split into multiple tables—such as Customers, Policies, Claims, and Sales Channels—you should create appropriate one-to-many relationships using common keys.

Verify that:

• Premium Amount is a decimal number.
• Policy Type is text.
• Sales Channel is text.
• Claim Status is text.
• Age Group is text.
• Processing Days is a whole number.

A clean and properly structured data model ensures better report performance and more accurate calculations.

Step 3: Create the KPI Cards

Return to the Report View and begin by creating the KPI cards displayed on the left side of the dashboard.

Insert four Card visuals and assign the following fields:

• Policies Sold
• Total Premium
• Total Assured Amount
• Claim Processing Time

Rename each card clearly and format the values using suitable number formats. Display Premium and Assured Amount as currency, while Claim Processing Time should be shown as the average number of days. Use a consistent font, apply rounded corners, and maintain equal spacing between the cards for a clean layout.

Step 4: Add Performance Gauges

Next, insert four Gauge visuals to monitor key insurance performance metrics.

Create gauges for:

• Policy Renewal Rate
• Net Promoter Score (NPS)
• Customer Retention Rate
• Policy Lapse Rate

Set realistic minimum, maximum, and target values for each gauge. Apply consistent colors and place these visuals beside the KPI cards so executives can quickly evaluate business performance at a glance.

Step 5: Build the Insurance Performance Matrix

Insert a Matrix Visual in the center of the report.

Use Policy Type as the row field and add the following values:

• Claim Settlement Ratio
• Underwriting Loss Ratio
• Combined Ratio

Enable row headers, apply alternating row colors if desired, and format percentage values with one or two decimal places. This matrix provides a detailed comparison of the performance of Disability, Health, Home, Life, and Travel insurance products.

Step 6: Create the Profit vs Expenses Chart

Insert a Clustered Column Chart.

Configure the visual as follows:

• Axis: Policy Type
• Values: Profit and Expenses

Use different colors for each measure so users can easily compare profitability against operational costs. Add data labels, enable the chart title, and adjust the axis formatting to improve readability.

Step 7: Build the Sales Channel Performance Chart

Insert another Clustered Column Chart to display the Annual Premium Equivalent (APE) Performance by Sales Channel.

Assign:

• Axis: Sales Channel
• Values: Premium Amount or APE

This visual compares premium generation across Agents, Bancassurance, and Brokers, helping users identify the most productive sales channel.

Step 8: Add the Policy Holder Age Distribution

Insert a Donut Chart.

Configure it using:

• Legend: Age Group
• Values: Policy Count

Power BI automatically calculates the percentage contribution of each age group. Enable percentage labels and place the legend neatly beside the chart for better readability.

Step 9: Create Interactive Slicers

At the top of the dashboard, add three slicers to make the report interactive.

Use the following fields:

• Policy Type
• Sales Channel
• Claim Status

Convert each slicer into a dropdown style to save space and allow users to filter the entire dashboard dynamically. Test the slicers by selecting different policy types or claim statuses and verify that every visual updates accordingly.

Step 10: Apply Professional Formatting

The final step is to polish the dashboard.

Add a descriptive title such as Insurance Dashboard at the top of the report. Use a consistent color palette throughout all visuals, align objects evenly, maintain equal spacing, and remove unnecessary gridlines or borders. Format chart titles, axis labels, and legends using the same font family and size to create a clean, executive-style appearance.

Finally, test the dashboard by interacting with each slicer and reviewing all visuals to ensure calculations are correct and filters work as expected. Save the report and publish it to the Power BI Service if you wish to share it with colleagues or include it in your professional portfolio.

By following these steps, you will create a fully interactive Insurance Dashboard that showcases policy performance, premium collection, claims analysis, customer retention, renewal rates, sales channel effectiveness, and policyholder demographics. This project demonstrates essential Power BI skills, including data visualization, dashboard design, business reporting, and interactive analytics, making it an excellent addition to any data analyst or business intelligence portfolio.