TOP
“The purpose of computing is insight, not numbers.” This quote from the mathematician Richard W. Hamming resonates today because the challenges around understanding and analysing huge amounts of data have grown significantly over the last few years. Even when using powerful systems and tools for automated data analysis, understanding - and visualising - analytical data is still problematic.
That’s particularly true in the insurance industry - and especially in claims management where claims assessment speed, quality and claimant experience are so important. Fortunately, the evolution of data visualisation techniques is making it possible to generate added value in areas such as claims operations.
Put simply, visualisation processes render static numerical values more tangible and therefore more comprehensible for the observer. It is the link between pure data management and complex data modelling.
Visualisation, with the help of Visual Analytics, allows anomalies, abnormalities and patterns to be detected and displayed multi-dimensionally. The results can be evaluated and interpreted not only by data scientists but also by other experts from business units. Visual Analytics therefore supports the transfer of knowledge into various parts of a company.
Visualisation isn’t an optimised controlling instrument, but rather an opportunity for collaborative exchange between internal departments.
Data Visualisation can be divided into three different subtopics: Information Design, Visual Business Intelligence (VBI) and Visual Analytics.
A big advantage of Visual Analytics instruments is that human creativity, cognitive understanding and expertise are combined with the analytical skills of a computer. The interaction of the user with the visualisation is necessary to make revealing information visible; for example, by zooming to different data areas or by viewing different multidimensional visual layers on the data.
Dashboards are a popular and useful tool for visualising claims processes. From an operational perspective, this can mean a visual display of claims case load and service times, potential enhancement of the preparation of audit reports, or flexibility in the monitoring of costs and growth rates. For insured losses, a dashboard helps with the direct evaluation of contract-related data because it can be visualised in an effective and efficient way.
Visual Analytics can be tailor-made for specific products. In Disability insurance, for example, dashboards can help to improve the presentation of an insured person’s information about his or her financial income situation and to highlight irregularities.
Visual analysis and interactive dashboards can create a visualised 360-degree view of a benefit case when enough basic data is available. This can also be used at the management level to monitor average cash values, processing times, or other external effects. A random accumulation of early claims, or the localisation of many claims from the same environment, are just two examples.
The insurance industry can no longer rely on time-consuming monitoring by employees, environmentally harmful reports in paper form, or unfathomable Excel tables. Reporting processes can (and will) be implemented much more efficiently and, above all, more clearly through the use of Visual Analytics.
Visual Analytics and its tools facilitate the combination of human knowledge and data analysis, which in turn increases the value of the monitoring and visualisation of complex and diverse data, displaying them in real time.
It is important to be aware of the significant requirements in design when developing a Visual Analytics solution inhouse. Alternatively, it might be preferable to use state-of-the-art business intelligence software from the beginning. Either way, the goal should always be to optimise the tool’s user-friendliness and thereby achieve a higher user acceptance rate.
If you have additional questions or are interested in further fields in the application of Visual Basic Analytics, please do not hesitate to contact me or my colleagues.
