How to Create an Insurance Dashboard in Tableau

Building an insurance dashboard in Tableau transforms raw policy, claim, and premium data into clear, actionable visuals. Instead of digging through spreadsheets, you can see performance at a glance and identify trends that matter. This guide walks you through the essentials, from defining your metrics to building an interactive dashboard step-by-step.

Graphed

Build AI Agents for Marketing

Build virtual employees that run your go to market. Connect your data sources, deploy autonomous agents, and grow your company.

Build Your First Agent

Before You Build: Defining Your Dashboard's Purpose

A good dashboard tells a story. Before you drag your first field, ask yourself what story you need to tell and who the audience is. An executive needs a high-level overview of profitability, a claims manager needs to track processing times, and an underwriting manager needs to monitor policy growth and risk. Your dashboard's purpose dictates the metrics you’ll focus on.

Start by identifying the key questions you need to answer. Examples could include:

• Which regions are generating the most claims?
• Are we setting our premiums correctly compared to claim payouts?
• How long does it take for us to process and close a claim?
• Which types of policies are most profitable?
• What's our customer churn rate month-over-month?

These questions help you pinpoint the Key Performance Indicators (KPIs) that are most important for your business. Common insurance KPIs include:

• Loss Ratio (or Claims Ratio): Calculated as (Incurred Losses + Adjustment Expenses) / Earned Premiums. This is a core metric for profitability.
• Claim Cycle Time: The average time from when a claim is reported to when it is closed.
• Policy Conversion Rate: The percentage of quotes that turn into bound policies.
• Customer Acquisition Cost (CAC): How much it costs to acquire a new policyholder.
• Number of Policies Written: A key growth metric showing new business volume.

AI Agents for Marketing

Crash Course

Graphed

Free PDF · the crash course

AI Agents for Marketing Crash Course

Learn how to deploy AI marketing agents across your go-to-market — the best tools, prompts, and workflows to turn your data into autonomous execution without writing code.

Download the PDF

Step 1: Connecting and Preparing Your Insurance Data

To get started in Tableau, you need data. For this example, let's assume you have data in spreadsheets (like Excel or Google Sheets), but the same principles apply if you're connecting to a database like SQL Server or Snowflake. Insurance data is often spread across a few core tables:

• Claims Data: Includes fields like Claim ID, Policy ID, Date of Incident, Date Reported, Date Closed, Claim Type, Claim Amount, and Claim Status.
• Policy Data: Includes fields like Policy ID, Customer ID, Policy Type (e.g., Auto, Home, Life), Policy Start Date, Effective Date, Premium Amount, and Coverage Details.
• Customer Data: Typically contains Customer ID, Location (City, State, Zip Code), Age, and Gender.

Getting this data into Tableau is straightforward:

1. Open Tableau Desktop and click "Connect to Data."
2. Select the appropriate connector (e.g., Microsoft Excel).
3. Find your file(s) and open them.

Once connected, Tableau will display the tables in the "Data Source" tab. If you loaded multiple tables, you can use Tableau's relationship builder (the "noodles") to link them. Simply drag the tables onto the canvas. Tableau is smart and will often create the relationships automatically if your column names match (e.g., Policy ID in both the Claims table and the Policy table). This allows you to analyze data across all tables seamlessly.

Step 2: Building Essential Insurance Visualizations

Now that your data is ready, you can start building the individual charts that will make up your dashboard. Let's create a few of the most impactful ones.

Visualizing Premiums Written vs. Claims Paid

This dual-axis chart shows the relationship between money coming in (premiums) and money going out (claims). It directly helps visualize your loss ratio over time.

1. Go to a new worksheet and name it "Premiums vs. Claims."
2. Drag Policy Start Date to the Columns shelf. Right-click it and select "Month" for a continuous monthly view.
3. Drag Premium Amount to the Rows shelf. Tableau will create a line chart showing premiums over time.
4. Drag Claim Amount to the Rows shelf, placing it next to the "SUM(Premium Amount)" pill.
5. You now have two line charts. Right-click the SUM(Claim Amount) pill on the Rows shelf and select "Dual Axis."
6. To make it easier to read, click the "Marks" card for SUM(Premium Amount) and change the chart type to "Bar."
7. Right-click on the right-side axis and select "Synchronize Axis" to ensure the scales match up.
8. Adjust colors and labels as needed. Now you can clearly see when claims spike relative to the premiums you've collected.

Graphed

Build AI Agents for Marketing

Build virtual employees that run your go to market. Connect your data sources, deploy autonomous agents, and grow your company.

Build Your First Agent

Creating a Calculated Field for Loss Ratio

While the visual above is helpful, a direct Loss Ratio metric is even better. You can create this using a calculated field.

1. Click the down arrow in the Data pane on the left and select "Create Calculated Field."
2. Name it "Loss Ratio."
3. In the formula box, enter the calculation:

SUM([Claim Amount]) / SUM([Premium Amount])

1. Click "OK."
2. Now you have a new metric you can use. To visualize it, create a new sheet, drag Policy Start Date to Columns (set to Month), and drag your new Loss Ratio field to Rows. This will give you a clear line chart of your loss ratio trend. Format the number as a percentage for clarity.

Mapping Claim Hotspots by Location

A map is the best way to see where claims are concentrated. This helps with risk assessment, targeted marketing, and resource allocation.

1. Make sure your geographic data (e.g., State or Zip Code) is identified as a geographic role. In the data pane, click the icon next to your location field (# or Abc) and set the Geographic Role to "State/Province" or "ZIP Code/Postcode."
2. Go to a new worksheet and double-click your State field. Tableau will automatically generate a map with a dot for each state in your data.
3. To make this map more useful, drag Claim Amount to the Color marks card. States with higher total claim costs will now be shaded darker.
4. Drag Claim ID to the Size marks card. Right-click the pill and change the measure from "Sum" to "Count (Distinct)" to size the dots based on the number of claims.
5. Hover over any state to see the fine details in the tooltip. You can edit the tooltip to show an exact summary of claims and costs.

Analyzing Claim Cycle Time by Policy Type

Reducing claim cycle time improves customer satisfaction and operational efficiency. A box-and-whisker plot provides a detailed view of its distribution, not just the average.

1. First, you need to calculate the cycle time. Create a calculated field named "Claim Cycle Time."
2. Use the DATEDIFF function to calculate the number of days between the report date and the close date:

DATEDIFF('day', [Date Reported], [Date Closed])

1. Go to a new worksheet. Drag Policy Type to the Columns shelf.
2. Drag your new Claim Cycle Time field to the Rows shelf.
3. Tableau might default to SUM. Right-click on the "Claim Cycle Time" pill and change the aggregation to "Dimension." This will show you a dot for every single claim, which is not what we want yet.
4. Click "Show Me" in the top right corner and select the box-and-whisker plot.

This visualization instantly tells you a lot. The box shows where 50% of your claims fall, the line in the middle is the median time, and the "whiskers" and any outliers show the full range. You can immediately spot which policy types have the longest or most inconsistent cycle times.

AI Agents for Marketing

Crash Course

Graphed

Free PDF · the crash course

AI Agents for Marketing Crash Course

Learn how to deploy AI marketing agents across your go-to-market — the best tools, prompts, and workflows to turn your data into autonomous execution without writing code.

Download the PDF

Building a Claims Status Overview

Key stakeholders need a quick summary of the open claims pipeline. A simple bar chart or treemap is perfect for this.

1. On a new worksheet, drag Claim Status to the Rows shelf.
2. Drag Claim ID to the Columns shelf, and right-click to change its measure to "Count (Distinct)."
3. You now have a simple, effective bar chart showing how many claims are Open, Closed, or in any other stage you track.
4. Add totals by going to the 'Analytics' pane and dragging 'Totals' to show Row Grand Totals.

Step 3: Bringing It All Together in an Interactive Dashboard

Once you have your worksheets, it's time to assemble them into a cohesive dashboard where everything works together.

1. Click the "New Dashboard" icon at the bottom of the screen (the square with a plus sign).
2. On the left, you will see a list of all the worksheets you built. Drag and drop them onto the dashboard canvas. You can arrange them in a tiled layout for a neat, grid-like structure.
3. Add Interactivity. The true power of a Tableau dashboard is its interactivity.
4. Include Key Metrics. Add some large, "at-a-glance" KPIs at the top using Text objects. Create separate worksheets for single "Big-Ass Number" (BAN) KPIs like Total # of Policies, Overall Loss Ratio, or Average Claim Payout and arrange them at the top.
5. Refine Formatting. Use consistent titles, colors, and layouts. The goal is clarity. Remove any unnecessary labels, lines, or details that might distract the viewer.

Final Thoughts

You’ve now walked through the steps to transform separate insurance data tables into a fully functional, interactive Tableau dashboard. By planning your visuals based on key business questions, building clear charts for specific KPIs, and adding interactivity, you've created a powerful tool that delivers real-time insights for better decision-making.

Creating detailed dashboards in programs like Tableau is a valuable skill, but it often requires a big-time investment, especially for teams who just need answers fast. That's why we created Graphed. We automate the entire process by connecting to your crucial data sources - whether it's advertising platforms, your CRM, or databases - and let you build reports and dashboards in seconds with natural language. Instead of taking a course on building visualizations, you just ask, "Show me a dashboard of premiums vs. claims by state for this year," and our AI does the heavy lifting for you.