Insurance Big Data Analytics Trends in 2020
When talking about insurance industry trends 2020, it’s impossible to miss big data insurance. In an area closely related to finance, there cannot be small amounts of information. The huge flow of incoming data is not only fast but also highly confidential. Ensuring the safety and security of every transaction is the main task of insurance companies. Another very important point is insurance data analytics. The more information needs to be processed, the slower this process. There is also the possibility of inaccuracies. Modern trends in the development of the industry are aimed at eliminating errors and speeding up the process of working with applications and financial flows.
Trends in Big Data for Insurance
Big data and insurance are inextricably linked. Modern companies are trying to implement technologies in several directions at once.
Machine learning
Collecting information and then analyzing it takes a lot of time and labor resources. Machine learning helps to replace human labor at least partially. This technology also allows you to work with historical data to be able to perform statistical analysis. End-to-end analytics of past and current data improves planning. The manual develops more deliberately:
- Pricing strategies;
- Advertising content;
- A plan for handling complaints.
Predictive Analytics
Big data in insurance helps you make more accurate profit forecasts. This is a very important part of the work of any company. Better analytics of past work experience allows for better risk assessment in the future. Automatic processing of large amounts of information has improved the work according to the following criteria:
- Calculation of prices for services;
- Assessment of risks for insurance of various processes, things, health and life of people;
- Work with claims;
- Development of new trends.
Data Privacy
The security of personal information about customers and all transactions is a prerequisite for the operation of every commercial organization. The legislation imposes strict restrictions on the dissemination of information about clients of insurance companies. The technologies used must be absolutely safe. Therefore, insurers often use the same protocols as the fintech sector. However, laws change frequently. This means that the algorithms used must be flexible in order to comply with legal requirements.
IoT
The introduction of artificial intelligence and IoT has led to an uncontrolled growth in data volumes. They need not only be stored in the system, but also skillfully analyzed. You also need to be able to extract the information you need at any time. But there are huge benefits too. For example, insurance companies that have introduced IoT into the work process received the following bonuses:
- Automatic risk assessment;
- Customizable regular reports;
- Automatic planning of marketing campaigns based on end-to-end analytics;
- Processing claims in real time without the possibility of data leakage.
How to Leverage Big Data in Insurance?
We have already come up with many tools, platforms and software products that allow you to operate with big data. But they should only serve as an example for their own development. Serious insurance companies should order software development for their needs, taking into account the goals and methods of work. You can read more about the new trends here:
https://blog.dataart.com/the-innovative-approaches-redefining-the-insurance-sphere.
Conclusions
The insurance industry needs high speed and absolute precision. Any mistake can cost the company not only losses due to customers leaving for competitors. A lawsuit can destroy a good reputation and make a business a failure. Algorithms for working with large databases help avoid errors and speed up customer service. Also, the use of IT technologies simplifies the filing of applications and creates an opportunity to offer users new types of services.
