After a decade of strong growth, the insurance industry is now grappling with slow growth, rising costs, deterioration distribution structure and stalled reforms. To top it all, most of the Insurance companies are having a High Expense Ratio, Loss ratio, the insurance margin has gone down and the minimum capital requirement has gone up. The Life insurance segment is witnessing a year-on-year decline whereas non-life segment is still struggling with underwriting losses.
However, the picture for the Insurance sector is not all that gloomy, if corrective measures are taken and implemented, we can witness a sea change of profit margins in the insurance sector. This can only happen if Insurance companies know how to optimize their Business Performance by using Analytics from which they are able to drive insights. While basic reporting and descriptive analytics continue to be a must have for insurers, advanced predictive and prescriptive analytics have now become pre-requisites for any insurance companies to succeed.
Researches have shown that Organizations actually process only about 10 to 15 percent of the available data, while managing this data can be challenging, but for insurance companies can reap benefits like increased productivity, improved competitive advantage and enhanced customer experience. Insurance companies have to realize that they need to be an objective driven organization to align their goals with their customers. This new strategy with the help of Analytics can help them derive insights that will maintain a competitive advantage and stay ahead of the curve.
Some of the ways in which Analytics brings value to the Insurance companies are:
1. Revenue Growth
Timely access to the Data, consolidated view of the data and analytics combined with advanced insights brings immediate benefits to the organization interms of benefits in Revenue growth. It improves the product, helps in segmentation, understanding customer and geographical analytics. Distribution channel performance measurement enables insurers to conduct focused campaigns to give them an advantage of their competitors.
2. Overhead expenses are reduced
With the advanced analytics and IT operations, Insurance companies can reduce heavily on their overhead expenses which don’t bring any business to the company. The Analytics dashboard reporting causes what-if analysis, forecasting, helps insurance companies to take informed, timely decisions and helps them prevent delays. This also helps in reduction in fines from regulatory bodies interms of inaccurate or incomplete data and delays.
3. Customer service improves
Another aspect where actionable analytics is advantageous is it helps companies give timely insight into operational metrics and enables them to properly address the concerns related to services and complaints of their customers. Having the advantage to see the granular details of the activities enables business users to optimize the business process and helps in customer retention and drive growth thus, improving the overall profitability of the company.
4. Reduction in fraud
Having a detailed analytics platform helps in reduction in fraud as the insurance companies can get a detailed report, it also helps in reducing any delay time that may result in any time in due diligence of any activity. Another major challenge insurance companies face is interms of Optimizing resource allocation, employee efficiency and productivity. Robust trending and forecasting capabilities helps define improved strategies and take adequate preventive measures.
Actionable Analytics is all the Insurance companies should definitely implement to get a better insight of all their unstructured data. Sophisticated Predictive and prescriptive analytics exist today that helps in improving an insurer’s probability of top-line and bottom-line growth, as well as manage risks and compliance. The critical question that these companies face nowadays regarding analytics is not “why analytics?” but “how to operationalize analytics?” The Insurance companies need to implement IT in their Business model whether it be interms s of Operational Analytics, or framing new strategies which may help them stay ahead from their competitors. Category : big-data