By Jean-Stéphane Faubert
Since the ultimate cost of their services is unknown when the contracts are signed, insurers can face the uncertainty of not knowing, in advance, how much they must charge, while nevertheless remaining bound by the twin requirements of profitability and competitiveness. A pricing Analytics solution can be used to mitigate the risk inherent in pricing insurance products. This article outlines three important characteristics of a pricing Analytics solution that, if considered from the outset and integrated into its fabric, will help any insurer steer it towards success in setting optimal prices.
The top-most factor influencing the success of a pricing solution is accessibility to an extensive set of relevant data. Pricing experts need direct, self-service access to all required data using specialized tools with which they are already familiar. Furthermore, the data must be stored in a form suitable for Analytics and it must be refreshed on right-time basis (i.e. at the most useful frequency). Pricing experts need to have a great deal of autonomy from the rest of the insurance business and should not have to rely on a third-party to gain access to the needed information, since this would negatively impact their efficiency in conducting investigations.
Meeting the accessibility requirements is straightforward enough, and is most easily achieved by constructing an analytical “sand-box” — an independent data mart dedicated to pricing Analytics endeavours.
The second characteristic of a successful pricing Analytics solution is its ability to enforce a set of data quality standards, namely: integrity, completeness, and traceability. Those in charge of pricing activities have a right to expect quality. Thus, it seems natural that a pricing Analytics solution should ensure the integrity, completeness, and traceability of the information it supplies to the business.
These standards can be defined as follows:
- Integrity – The information brought into the solution was not corrupted either up-stream or within the Analytics solution itself;
- Completeness – All the information was processed, hence nothing was lost;
- Traceability – Any piece of information can be traced back to its source.
The third defining characteristic of a successful insurance pricing Analytics solution is performance. The sad reality is that performance is often considered as an after-thought. It’s a shame, because the workflow of a pricing analyst typically involves working with huge volumes of information in a “trial-and-error” mode, seeking patterns and correlations from amongst enormous data sets. The reality in Analytics is that the most important performance gains are made in the design phase of solution development. The design of an Analytics solution should not only focus on making the solution work, but on making it work well and efficiently.
Most insurers face similar challenges to those touched on above when it comes to performing their pricing programs. By keeping the key characteristics of a successful pricing Analytics solution in mind — accessibility, quality, and performance — one is naturally led to extract more value from the pricing Analytics solution. For more characteristics about the design of a pricing Analytics solution that delivers value and ROI to your business, we invite you to read the following white paper: .
About the author
Jean-Stéphane Faubert is a Senior Solutions Architect at InEdge. He has more than 20 years experience designing and implementing information technology solutions. For more than half of his career, his focus has been in the design and implementation of Analytics solutions. Over the years, Jean-Stephane has designed Analytics solutions for clients in several industries, such as Insurance, Banking, Brokerage, Health, and others. His expertise covers the whole spectrum of Analytics project-specific tasks ranging from strategic planning, solutions architecture, project management, and assessment, all the way down to data modeling and detailed design.
About InEdge
InEdge is a leader in Insurance Analytics solutions. Experienced at quickly leveraging data, InEdge seamlessly and powerfully creates business advantage for its clients. Since its creation in 1994, InEdge has designed and implemented some of the most sophisticated analytical applications available today. Our clients add up to an impressive roster of Property & Casualty and Life Insurance companies. Our Analytics solutions improve and make easier decision-making at all levels for our clients.
Source: InEdge
