Four ways insurance benefits from business intelligence
Every day, businesses are discovering new ways to tap into the power and potential of big data. Due to access to unprecedented amounts of information on business performance and consumer behaviour, companies are now able to refine their products and services in limitless ways.
The insurance industry provides a good example of data being leveraged to help make beneficial business decisions. Since this industry is based on risk, it’s a natural fit for business intelligence (BI) and analytics.
The decision to take out an insurance policy, by both commercial and personal customers, is based on the likelihood of an adverse event occurring and negatively affecting them financially. Insurers offer coverage to customers based on a number of factors, which together can be used as an assessment of the cost of covering any claims.
The industry is both people-centric and data-rich, meaning that insurance companies are in an ideal position to refine their business practices by utilising modern data analysis. Specifically, there are several key operational areas within an insurance company that can be transformed using modern analytics techniques.
For insurance sales teams, the ability to make fast and accurate recommendations is vital to success. Sales representatives need information at their fingertips while on site with brokers or clients—whose needs constantly change. For this reason, moving to a mobile solution is inevitable. Traditional sales solutions are not equipped to handle the needs of a modern sales team and legacy systems fall short by failing to provide in-depth insights into individual customers or prospects when they are required.
Mobile access to resources provided by modern BI tools now provide sales representatives the insights at that crucial time, boosting productivity and providing a competitive edge. The type of content that is readily available includes context-aware maps that help determine which account to visit next, multimedia content, like sales presentations and training videos, and real-time access to quote analysis, buying patterns and demographics.
For insurance professionals dealing with claims, fraud detection is critical. The ability to spot inconsistencies helps insurance companies identify suspicious cases and avoid costly pay outs for fraudulent claims. However, fraud perpetrators are becoming more sophisticated and are able to manipulate most rules-based fraud solutions on the market today.
That’s where predictive analytics can help. Armed with deep insight into their claimant pool and powerful exception-based reporting, insurance companies can identify fraud sooner and more effectively at each stage of the claims cycle. These predictive models use a powerful combination of rules, modelling, database searches and exception reporting that is more difficult to maliciously manipulate.
