The age-old adage “a picture is worth a thousand words”, is proven true time and again by data visualization tools. These tools highlight trends in data that would have otherwise been invisible to the naked eye. One platform is Tableau, which is currently a tool used in multiple industry verticals where huge volumes of data need to be visualized in a matter of seconds.
There are many business intelligence tools with data visualization, like IBM Cognos, Microsoft’s BI tools, SAPs Business Objects, Oracle’s BI, and there are specialized data visualization tools like FusionCharts, Google Charts, Infogram, etc.; but why is this new product, Tableau gaining attention?
Tableau brings together data visualization and databases through the use of a proprietary technology called VizQL. VizQL statements describe an infinite class of sophisticated and useful visualizations. This technology is a unification of computer graphics and databases. This fundamentally new architecture does for data interactions in visual form what SQL did for data interactions in text form.
How does Tableau help in insurance analytics and data visualization?
Claims analysis refers to the mechanism how claims are settled. Claims could be submitted by various categories of users (physicians, automobile users, etc.), from various locations, and by various modes (phone, web, physical claims).
How do the ratios of claims settled among these categories vary? Are claims submitted by physicians cleared more frequently compared to claims from vehicle users? Within claims from physicians, are claims over the web settled differently?
Insights such as these help managers, brokers and administrators alike quickly identify where they can optimize resources, and improve claims processing procedures.
Premium forecasting is based on historical data. In a typical employer sponsored health insurance scenario, multiple factors such as gender, age, region, health status, along with historical data influence the premium for the future. Traditional forecasting involved going through several spread sheets of data, but with Tableau, with its drag and drop functionality; users can adjust these criteria and others to see historic trends and projected costs.
Analysing settlement data can help identify fraudulent claims. But many a time, analysing this data is time consuming. Using Tableau, out of pattern behaviour during claims processing can be brought out in a matter of seconds, helping field agents receive details of this behaviour on their device.
Year on year comparisons on revenue are a basic element of revenue comparison so far as insurance managers and underwriters track, to help them take decisions for the future.
Earlier comparisons were across multiple rows of tabulated data reports, but with Tableau, an interactive time series report with drill down facility is available for identified users.
While the above capabilities touch upon the operational aspects of insurance analytics using tableau, it can also be used for management reporting:
Executive dashboards from Tableau give a view of the business from three perspectives:
(a) Profitability by product category, geography and customer segment
(b) Product performance, and
(c) Customer segment performance. Each dashboard comes armed with visual drill down capabilities, making it easier for management decision makers to have both a bird’s eye, as well as a grasshopper eye view of the business.
Track operational insurance metrics
Tableau can also be used to set up a whole range of industry standard, as well as organizational specific insurance metrics such as:
- Insurance reserves
- Unearned premium
- Stated & unresolved damages
- Doubtful debts
- Portfolio performance
- KPIs for modelling profitable insurance products
Insurance industry has seen a big shift in the usage of this software, and with Tableau going public it will only give more confidence for their customers.
With the world moving fast towards a ‘big data’ driven eco-system, Tableau and its capabilities in data visualization represents an important platform for decision making. The proliferation of NoSQL, or schema-agnostic databases that house all type of data such as email, documents, structured values, machine data, social media and more, and Tableau’s capabilities on integrating with such data sources is another key driver for the insurance industry to adopt Tableau. Using these capabilities, insurance customers can visualize:
- Open text fields in CRM/ERP systems
- Customer sentiment by correlating social media data with point-of-sale systems and websites
- Regulatory compliance reports based on data from disparate systems