8 April 2024 2 min read

🤖 AI in reinsurance : What, how, and why ?

Reinsurance Tutorials #15 - Season 3

Hi everybody 👋


Today, and for the 15th Reinsurance Tutorials video of the season, we will talk about the " AI in reinsurance : What, how, and why ?"


This subject will be addressed by CCR Re experts Jérôme Isenbart and Akli Kais.


Let’s start! 

[Akli Kais] : Hello and welcome to this serie of tutorials on AI in reinsurance.


[Jérôme Isenbart] : Hello, I am Jérôme Isenbart, I will be Akli’s duo for this presentation.


[Akli] : Today, we will be discussing a topic that has been making waves in the modern world : Artificial Intelligence, or AI. Specifically, we will be exploring the what, the how, and the why of the use of AI in the reinsurance industry.


What is AI?


[Akli] : First off, what exactly is AI? Simply put, it is the use of computer systems to perform tasks that would normally require human intelligence, such as learning, reasoning, and problem-solving. Think of ChatGPT for generative conversation, Shazam for music recognition, Amazon AI system for book recommendation and moreover Tesla self-driving technology.

AI systems are designed to analyze and interpret large amounts of data, learn from experience, recognize patterns, adapt to new situations, and identify insights that humans may not be able to discern, enabling them to make predictions and perform tasks autonomously.

There are several types of AI systems, the most used in reinsurance are:

  1. Rule-based systems: This type of AI uses a set of predefined rules to make decisions based on input data. Rule-based AI are simple to understand but complex to maintain over time. This type can be used in applications such as chatbots and decision support systems.
  2. Then we have machine learning, which uses statistical models to identify patterns in historical data and make predictions, like pricing claims and portfolio optimization.
  3. And the most used one in reinsurance is deep learning which is a subset of machine learning that uses neural networks to learn complex interactions in data in different forms for applications such as natural language processing for text understanding, image, and video recognition.

Overall, these different types of AI are designed to solve distinct problems and achieve different objectives and can be combined to create more sophisticated AI systems.


How is AI used in reinsurance?


[Jérôme] : Now, how exactly can AI be used in reinsurance? There are several applications that we will explore.

Firstly, AI can be used for risk assessment by analyzing a wide range of risk factors, including historical data, market trends, and emerging risks to make accurate predictions about the likelihood of a claim. This helps us to better manage our risk exposure and ensure that we are charging appropriate premiums for our clients.


Secondly, AI can be used for legal clauses and underwriting by automatically identifying and extracting specific information from contractual documents such as policy numbers, provisions, dates, and names of insured parties. By doing so, we reduce the risk of errors and inconsistencies. This also improves the overall efficiency of the underwriting process by freeing up the underwriter’s time to focus on more complex tasks.


Another example is catastrophe modeling. With AI, we can simulate and analyze different scenarios for catastrophic events, such as hurricanes or earthquakes. We can also use satellite images to monitor drought impacts to better understand the potential impact of these events on our portfolio.


Finally, AI can be used for decision-making by processing massive amounts of data in a fraction of the time it would take humans to, for example, intelligently search specific type of clauses in all contracts of our portfolio and compare them within the market standards. This can help boost our domain knowledge, stay ahead of the curve, and respond to changing market conditions more quickly.


Why is AI used in reinsurance?


[Akli] : As we have seen through the different use cases, using AI in reinsurance provides several benefits: better decision-making, increased efficiency and accuracy, better risk management, enhanced customer service and, of course, we proved that it works at CCR Re.


[Jérôme] : In conclusion, AI is a technology that has the potential to revolutionize the world of reinsurance and if you are in this industry, it is time to start thinking about how AI can help you achieve your goals and better serve your clients. Thank you.


[Akli] : Thanks a lot for watching the video.


[Akli/Jérôme] : And Goodbye. 




Bye for now 👋

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