Tableau for Insurance Analytics
Tableau outstanding and remarkable features and services are what make it the perfect tool for improving profitability and simplifies your works. The insurance industry is chock-full of data ready for analytics and reporting. But equipping stakeholders in your organization to effectively analyze and use that data in a timely manner has been a challenge. Use Tableau to:
Understand how your sales organization is performing.
Investigate claims patterns to detect probable fraud.
Monitor claims processing status.
Evaluate overall portfolio risk profile in single dashboard.
Create pricing models that let you interactively explore scenarios.
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[tabby title="Claims Analysis"] Investigate claims interactively to see patterns for action Does a claim submitted by a physician have a different claim paid ratio than those submitted by phone or web? You bet. Is it valuable to dig into these differences to make more informed decisions? Absolutely. Don’t stop there. Couple this claims information with other salient data. Which call centers are processing the claims? How does claim status vary by region, by call center? Insights such as these, illustrated in the visualization to the right, help managers, brokers and administrators alike quickly identify where they can optimize call center resources, improve claims processing procedures and identify potentially fraudulent patterns. Click on the visualization to see how claims status varies by region and how the claim was initiated. Tableau[tabby title="Premium Forecasting"] Visualize historic data to estimate cost impact Using historic data to estimate future premiums isn’t new. But creating an interactive report that facilitates quick insight to forecast these costs is not a common feature in most insurance reporting tools. Don’t limit yourself to a slide deck that only shows top-line estimates or spend time wading through dozens of spreadsheet tabs looking for answers. By using Tableau to create an interactive report that’s right for your needs, you can quickly be evaluating your options and future costs, not waiting for a new round of analysis. This sample report makes it intuitive to ask – and answer – real-time questions about how projected costs for an employer could vary based on several factors. Gender, age, region all affect estimated costs. Click on the visualization to adjust these criteria and others to see historic trends and projected costs. [tabby title="Fraud Detection"] Quickly show outliers and suspicious patterns in your data The data you need to reveal fraudulent activities exists within your organization. However, analyzing it in a meaningful way to detect out-of-pattern behavior in a timely fashion has been next to impossible. Tableau lets you point to nearly any data source and immediately begin visualizing it to see behavior that’s amiss. Once a potential issue is identified, hand off the dashboard to your field investigators who can access it on a mobile device. Now fully equipped with the right data, he can pick up the thread of suspicious behavior and resolve it quickly. Click into this report and adjust the filters to find claims that fall outside normal bands. Where would you focus your investigators? [tabby title="Revenue Comparison"] Drill into specific, code-level detail in two clicks Year-to-year comparisons are a basic, but essential element to insurance analysis. Agents, underwriters and managers alike rely on historical data to gather intelligence for forward-looking decisions. In this report, you can select a set of codes based on alphabetical grouping then determine a region of interest. Using the scroll bar, any claims code can be reviewed at a glance. Not only are the minimum and maximum payouts for each code highlighted, viewers can mouse over any point to get detailed information on a specific claim. The impact of a straightforward, yet interactive time series report such as this gives more information much faster than could be gleaned in a table. Click on it now, select a set of codes and a region to explore. [tabbyending] Source: