Data Analytics Is Changing Insurance Industry For The Better. Here's How.
By Ray Parker
Whether you are planning to buy a property or buying a car or simply want to secure your future, you need insurance at one point in life. The insurance industry is based on one fundamental process and that is risk management. Efficient risk management is done via data and in today’s world, the insurance industry is brimming with data. The data is both structured (coming from emails, excel sheets, etc.) and unstructured (social media, newspapers, newsletters, etc.). Through efficient data analytics, insurers can not only have more in-depth insights into their customers but also can have a competitive edge among other insurers. No wonder why thousands of tech giants are investing millions in data analytics to be used in the insurance industry. Here’s how data analytics is reshaping the traditional insurance industry for the better.
More Customer-Centric
According to experts, personalization brings revenue. Insurance companies nowadays are becoming more and more client-centric for all the right reasons. Based on client data collected from their activities on social media, their lifestyle standards and comparing it with the previous data of similar clients, insurers can offer them personalized services according to their preferences. Insurers can also be aware of clients at high risk of canceling their policies and work on strategies to avoid that.
Fraud Prevention And Detection
Filling fraudulent claims is a challenge faced by every insurer today. Fraud detection and prevention can be more effectively managed by analyzing data related to the customer’s history. It can help insurers estimate which clients are more likely to put a fraudulent claim before they even file it. For example, agents can observe their clients’ social media activities and collect relevant data periodically. So, if a client files a claim, analysis can be done on pre-recorded data to provide a clearer picture of whether the claim is valid and authentic or not. For example, if a client posts pictures of his Dubai Marina apartments after-party, and after a few days, files a claim of any damaged being done to the property around the same days, it can be a good indicator of it being an invalid claim and insurers can dig deep into details.
Efficient Underwriting
In underwriting, the main goal of an insurer is to collect more premiums and generate more income than it is expected to be paid in case of a loss. This must be done while keeping the premiums and pricing reasonable enough for potential clients to buy. Using data analytics in underwriting, insurers can get insights into the potential client and their lifestyle by analyzing the data gathered from their social media and other sources of information. In property insurance, for example, if someone has their Arabian Ranches villas for sale, using advanced data analytics will give underwriters insights of future appreciation or depreciation of the property, similar claims that got filed belonging to the same region and any hidden risks that might need attention in future.
Future-Proofing
Predictive analysis is the future of Data Analytics. Using advanced data analytics with predictive analysis, insurance business can estimate whether their book of business is profitable or not, is there any alteration required in sales practice to increase that profit, what are the reasons why operations are getting delayed, ways to overcome it and reduce wasted time with policyholders, increase revenues and maximize overall performance of the company.
In a nutshell, data analytics is here to stay and is aimed to take the insurance industry forward. Embracing it will result in a more accurate, quick and fair way to deal with insurance.