Insurance and data-driven what's changing

The insurance market is known to be one of the most traditional and conservative sectors in the use of innovative technologies.
However, something has changed in recent years: more and more companies are adopting a data-driven approach based on the collection, analysis and interpretation of data, to improve their operations and provide customers with an increasingly personalized service.
According to the recent report released by the Capgemini Research Institute, 40% of insurers currently use data to access new markets, while 43% have modernized and enhanced their risk management algorithms.

There is still a long way to go: according to the latest survey conducted by IVASS on the use of technologies (machine learning) by insurance companies in their relations with policyholders, it emerges that in reality companies are still in a phase initial knowledge and adoption of these innovative tools.
Only 27% of insurance companies use machine learning algorithms when dealing with customers.
The areas of use of the algorithms are: fraud prevention, claims management in the R.C. car and the identification of customers' intentions to abandon, also for pricing purposes upon renewal of the policy.
There are still many challenges ahead for insurance companies although many companies are investing in data-driven technologies such as artificial intelligence (AI) and machine learning (ML), in order to improve their ability to analyze large amounts of data and use this information to make more informed and timely decisions. 

To date, however, only 18% of companies have the technical and practical capabilities capable of supporting data-driven programs that allow them to make the most of the growing volume of data.
So, in detail, what are the aspects of the data-driven approach that make it a source of competitiveness that can really make a difference in the insurance sector?

One of the main advantages of the data-driven approach in the insurance market is the possibility to better understand the different risk protections associated with insurance policies.
Data analysis can provide detailed information on the risks associated with specific activities, customer behaviors, market trends and climatic conditions that can affect the probability of a claim.
All this information can be useful for insurance companies to create "tailor-made" policies for their customers, which cover exactly the risks to which they are exposed, avoiding overcharging or underestimating certain situations, which can affect the company's profitability.

 Cost reduction for companies
Another advantage of the data-driven approach is the possibility of reducing the operational costs of insurance companies. Data analytics can help identify areas where spending items can be reduced, such as claims management and marketing optimization. This cost reduction can translate into cheaper rates for customers, improving the competitiveness of the companies themselves on the market.
Fraud prevention in the insurance market
As we said before, another advantage of the data-driven approach in the insurance market is the possibility of preventing fraud. In fact, data analysis can help companies identify suspicious behavior and anomalies in claims, identifying cases of fraud, reducing any losses resulting from damages and adopting preventive measures to prevent future occurrences.
Improved claims management
The data-driven approach in insurance can also improve claims management in the market. Data analytics can help companies identify problems in claims handling processes and take preventative measures to prevent future occurrences.
Insurance and competitive advantage
Finally, the use of data can provide insurance players with a competitive advantage over other players in the industry. For example, companies using the data-driven approach can identify new markets or offer innovative products, based on the data collected, and optimize business processes, using data to make informed decisions and achieve their business objectives.