Insurance has always used data to adapt its offer and anticipate claims. But with the advent of Big Data, insurers are faced with titanic volumes of data. To analyze and exploit this information, traditional actuarial methods are no longer sufficient. This is precisely why Data Science is making its way into the insurance industry.
How is risk prevention "calculated" in the insurance industry?
If insurers are to compensate the victims of claims, they must remain profitable if they are to maintain a sustainable business. In this respect, risk prevention is one of the major challenges facing all insurance companies.
It enables them to act on two levels. Firstly, by reducing the impact of a claim on an insured party. Secondly, by adapting the range of products and services on offer to current risks. As insurance is based on the principle of mutualization, organizations must find the right balance between the amount of contributions paid by all policyholders and compensation in the event of a claim. In this way, insurance remains profitable.
There are many different types of insurance risk, depending on the specialty concerned:
- Health: on average, 20% of policyholders account for 80% of expenditure.
- Natural disasters: far from being unpredictable, these climatic events can be anticipated to limit risk.
- Accidents: here again, a number of indicators can help insurers anticipate claims, such as driver behavior and experience behind the wheel.
etc.
To anticipate all these risks, insurers have always relied on available data. But in a fully digitalized world, insurers need Data Science more than ever.
What type of data does the insurance company collect?
In the age of Big Data, insurance companies have a wide variety of data at their disposal. Here are just a few examples:
- Weather data: to anticipate natural disasters.
- Connected objects: whether in the car or in the home, the Internet of Things provides a better understanding of policyholders’ habits and the associated risk. In this case, the insurance company must, of course, obtain the policyholder’s explicit consent.
- Digital pathways: through navigation on the website, social networks and the customer space, …. insurers have access to a wealth of digital information to analyze their policyholders’ behavior.
While this data is an invaluable tool for insurance companies, the key is to know how to use and interpret it. This is precisely why the role of Data Science in the insurance industry is gaining in importance.
The role of data scientists in the insurance industry
Originally, actuaries were responsible for analyzing risks in order to provide their clients with the most appropriate products and services. To this end, they carry out economic, financial and statistical studies.
But with the development of Big Data and the enormous volumes of data available, knowledge of purely insurance-related data is proving insufficient.
And with good reason: insurance companies now have access to data from a multitude of sources and in a wide variety of formats. In order to analyze this data, it is essential to master the tools of Data Analytics and Data Science. This is precisely why Data Scientists are joining the insurance industry.
Thanks to their expertise and their mathematical, statistical and IT skills, data science experts provide invaluable assistance to insurance companies:
- The exploitation of large masses of data: data scientists are able to interpret volumes of data that cannot be exploited through traditional actuarial methods.
- Predictive analysis: using Artificial Intelligence and Machine Learning, they can detect weak signals and facilitate decision-making.
- Visualization: through visualization and reporting tools, they make all types of data comprehensible to insurers (even the non-data literate).
All these skills enable insurers to define the best cover and offer the best rate according to the risk associated with each customer. And they do so with the utmost precision.
Data scientist and insurer, a true collaboration
The Data Scientist is not an insurer. So, while he provides insurance companies with a fresh, data-driven eye, he does not benefit from the business expertise of actuaries. Its role is not to replace insurers, but to support them through its analyses and recommendations.
As such, close collaboration between insurers and data scientists is necessary to improve the quality of services, the definition of offers and the relevance of decisions taken.
That said, given the growing importance of data science within the insurance industry, a new profession seems to be emerging: that of digital actuary. The idea is to combine the Data Science professions specifically for the insurance world. In this way, the digital actuary not only masters all the tools of predictive analysis and data processing, but also all the rules specific to insurance.
Data science at the service of insurers
Improving offers, profitability, personalizing the customer experience, reducing risks… Data Science is at the service of the insurance industry. The convergence of these two disciplines is helping to reinvent insurance, making it more modern and closer to policyholders’ needs.
Allianz chooses DataScientest to train its employees in Data Science
Following an invitation to tender launched in 2017, Allianz, a major European player in the insurance sector, chose DataScientest to provide data science training for its employees.
Thanks to an innovative approach to learning, blended learning, which combines both online learning (e-learning) and videoconference mastercalss with in-house trainers, DataScientest has succeeded in adapting its distance learning to the company’s needs, while offering personalized follow-up for each learner.
The students’ professional projects have even won awards from the Argus de l’Assurance.
This partnership between Allianz and DataScientest is a successful example of how major companies and innovative startups can work together to develop key skills in constantly evolving fields.
