Insurance Data Analytics for Better Decision Making

Data is a gold mine in the hands of insurers and using it the right way is what significantly changes the game of competition in the insurance industry. Some researchers predict that the power of Big Data in the insurance spectrum is yet to unleash itself in all its energy. Moving towards it, the insurance incumbents are finding ways to transition unstructured data into meaningful insights that help them with decision-making more efficiently with the risk measures constantly changing and evolving.

Insurance Data Analytics is one of the ways forward for insurers, underwriters, and risk managers to ace the decisions of premium and risk calculation. The internet has widened the scope of data like never before and the unstructured data available even on social media could be of great importance to insurers. But to leverage the right data into relevant insights, insurers need to access the Big Data, this is where the power of insurance technology comes in. Insurance Technology is making strides in the competence of working on insurance data analytics and insurers are able to move forward with the push of insurtech and essential partnerships with insurtech companies.

Here are the ways in which Insurance Data Analytics is taking up the role of changing the insurance industry and innovating its decision making:

1. Managing Claims

The industry has suffered a huge cost to fraudulent acts in the past and with the entry of use of insurtech in predictive analysis, frauds have been minimized to a remarkable low. This portrays the accuracy of insurance data analytics by insurance technology. Identifying the applicants who are likely to commit fraud becomes easy for the insurers by analysis of Big Data at the underwriting stage only. When a customer registers a claim, insurers tend to audit the legitimacy of the claims where data from internal and external sources like even social media and digital channels are used to provide relevant insights.

2. Calculating Risk

Insurers have a crucial role of underwriting and they work on designing policies with utmost research and analysis. Insurance data analytics is the base for any policy-making for underwriters. For example, a person’s address, area of residence, and distance from a fire station are minimal data that insurers use for policy-writing but today when risks have increased and developed in quality from several factors, insurers dig deeper even in unstructured data of person’s social media to analyze the data for accurate decision-making.

3. Leveraging Customer Insights

A global customer survey conducted in 12 countries by Morgan Stanley and BCG reveals Insurance customers are now looking forward to digitalizing their insurance experience completely. In the world of the internet that we live in today, it is not easy to keep up with customer demands. But having access to relevant insurance data analytics is the key for insurers to rightly predict the customer behavior with the concern of the insurance policies they are offering or about to offer. Customer acquisition becomes simple once insurers can dig into what the customer requires, and Big Data analysis is the way for predicting that.

4. Balancing Competition in Customer Acquisition and Profits

The industry is packed with insurers competing toe to toe and it is not easy to acquire the customer at low cost and at the same time, earn better profits. So the target of insurance carriers and organizations is more on balancing the competition in customer acquisition than before. This is because in order to enhance customer acquisition, insurers need to lower the cost but it will reduce their profits. Insurance data analytics gives the strength to boost decision making of the insurers in a way that they leverage data to have the best of both the worlds, i.e., managing customer acquisition and profits at the same time. This is possible by partnering with the best insurance technology solutions for easing Big Data analysis.

Conclusion

Insurance data analytics empowers the insurance organizations and carriers to measure the best outcomes of the decisions they would make and hence, synthesize their decisions in the most progressive way possible. Besides, data analysis in the insurance industry helps insurance companies in adhering regulatory requirements and lowers the costs with efficient results visible in their profits. Excelling in Insurance data analysis is possible with leveraging the right insurance technology solutions.