The insurance industry was always heavily dependent on data. It used various information to evaluate risks, set prices, and overcome competitors in a rather tight niche.
But computing speed and a constantly increasing volume of data required changes and motivated insurance companies to delve deeper into modern technologies.
In this article, we want to share 10 ways in which data analytics may transform the insurance market in the current year and explain why it is so important. After reading this detailed overview, your insurance business will never be the same.
The world has never had as much information as there is now and businesses can’t manage it without turning to modern data analytics (DA) tools.
Insurance companies are not an exception and they use DA in literally every area from risk assessment and insurance pricing to fraud detection and prevention of claim cases. Some other examples of data analytics usage include targeting prospects, tracking sales, and studying consumer behaviour.
Insurance companies can even analyze and process information that at first may seem irrelevant but can significantly impact the final decision. For example, neighbourhood claims or weather patterns.
Data analytics is crucial for the insurance industry because it offers valuable insights for all participants of the process: insurers, agencies, and customers. Access to real-time data allows insurance agents to meet the needs of their customers in a fast and accurate way.
Data analytics allows insurance companies to collect and analyze huge amounts of information from hundreds of sources – preferences, risk factors, behaviours, and so on.
In 2023 and the upcoming years, insurers can use the latest algorithms to create insurance policies and prices based on personal characteristics, health, driving behaviours, and other issues.
More and more insurers use virtual assistants, AI customer support, and chatbots to provide their users with real-time assistance, streamline complaints, and offer personalized solutions.
With access to machine learning tools, insurance companies can switch from one-size-fits-all patterns to individual journeys which significantly boost user satisfaction and loyalty.
Telematics is a rather new term that embodies a blend of telecommunications and informatics. This science is used for monitoring cars, fleets, equipment, and other devices using GPS technology. It is mainly used for vehicle insurance whether it comes to selling and buying or sharing information about the owners.
Telematics can help insurance companies get a better understanding of the risks that individual drivers face on a daily basis.
Just think of it: advanced driver assistance systems and GPS generate huge volumes of information like average speed, driving behaviour, and braking patterns. With the help of this information, insurers can identify high-risk drivers and offer them advanced coverage options. Or decide whether to grant them insurance or not.
In addition, telematics is used to predict and reduce risks which, in turn, results in optimal coverage packages. This science is priceless for insurance companies that want to remain competitive and help all categories of drivers.
In our opinion, this might be the most important reason for turning to data analytics in 2023, 2024, and any other year. Data analytics can provide insurers with a profound understanding of various risk profiles and improve their underwriting processes. They may even use machine learning and artificial intelligence to evaluate risks and reduce overpricing.
Another crucial reason is detecting and preventing different sorts of fraud. By analyzing claims and customer behaviours, insurance businesses may identify potential harms at an early stage and take timely action. Moreover, modern instruments can monitor fraud in real-time and prevent it even without any human interference.
And let us not forget that data analytics can be vital for data security. Although with increased data collection come more privacy concerns, insurers and customers are more eager to comply with GDPR and other regulations which leads to market stability, privacy, and safety.
Embedded insurance integrates seamlessly when a customer purchases a product or service. For example, health insurance when booking a cruise or auto insurance when renting a car for a holiday trip. Embedded insurance can be done through partnerships of insurers with travel companies, car-sharing businesses, retailers, and other enterprises.
As you understand, such partnerships may have lots of risks considering the number of parties involved. But not with data analytics. Modern tools can collect, store, and process information about all partners to maintain trust and transparency in the relationships. It is a win-win situation both for insurers and customers and can potentially save them lots of money and nerves.
In the past, when someone wanted to insure their land or required a risk management survey, insurers had to travel on-site. This took hours or even days and involved unnecessary expenses on petrol and accommodation.
Thanks to data analytics and modern technologies, this process is much simpler and cheaper. We are talking about imagery and geospatial technologies like sensors, cameras, drones, and satellites. With their help, insurers get the necessary information about the environment and possible risks without the need to be actually present on site.
Sounds difficult? Let us give you a few examples. Imagery data can help with evaluating the possibility of natural disasters and geospatial data with accessing traffic patterns. Together, they contribute to accurate insurance coverage and better solutions.
With the help of these technologies, insurers can also collect valuable data for potential risks. For example, an overhanging tree or cracks in the road. Customers can also gain an advantage from imagery and geospatial technologies because they can get real-time updates and faster communication with carriers and insurers.
Do you remember the times when the insurance industry relied on papers? Thousands of documents were collected, scanned, printed, and stored in desks and shelves making the lives of insurers unbearable. Paperwork comes hand-in-hand with customer irritation, delays, and risks of making a mistake.
Luckily, in 2023 you will hardly find an insurance company that doesn’t use digital data instead of paper documents. The faster it can collect and process data, the better market positions it occupies.
Just think of how easy it is to store and find the necessary document or file when it is stored on a distant server. You can share it with colleagues, leave comments, request electronic signatures, and don’t stress out about possible data losses.
Even a decade ago, the insurance market was rather reserved – there were common policies and offerings to most categories of customers.
But thanks to the data from the Internet of Things and advanced machine learning, insurance companies improve their products not only in terms of personalization but in terms of functionality and diversity.
Just look at their websites – there are tens of filters to choose from and all this became possible thanks to huge amounts of collected and processed information.
Another less common but still extremely useful advantage of data analytics for insurance companies is related to the growing risks of climate and natural disasters. Year after year we witness significant changes in ecology, global warming, and earthquakes that may cause irreplaceable damage.
With the help of advanced climate modelling and assessment, insurance companies can manage catastrophe risks more efficiently and provide customers with additional offerings based on their geographical location or travelling history.
The last two advantages might not be directly related to data analytics but they emerge from the points discussed above.
When insurers offer customers personalized solutions and exceed their expectations, most likely they will surpass the competitors and occupy firmer positions on the market. By collecting data about the target audience and other insurance companies, you can gain loyal customers who will return to you over and over again.
The final point on our list is the growth of your company which is inevitable if you use data analytics to the maximum.
Better user experience, fraud protection, minimization of risks, product optimization, lead generation, and other topics discussed above will transform in higher revenues, better reputation, and expansion. Insurance companies that use data analytics see results rather quickly and ask themselves only one thing: ‘Why didn’t I start earlier?’
According to the 2022 Insurance Industry Outlook, 67% of insurers plan to increase their investments in data analytics. This technology is constantly evolving and its contribution to the insurance industry is growing at a fast speed.
Companies can improve user experience and offer personalized solutions, streamline operations, boost security, prevent fraud, and solve a bunch of other important problems. In the upcoming years, we expect more and more insurance companies to use the benefits of data analytics tools to get valuable insights from customer data.
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