AI In Insurance Use Case #4: Descartes Underwriting

  • 24 June 2019
  • Sam Mire

This interview is part of our new AI in Insurance series, where we interview the world's top thought leaders on the front lines of the intersections between AI and insurance.

In this interview, we speak with Tanguy Touffut, co-founder and CEO of Descartes Underwriting, to understand how his company is using AI to transform insurance, and what the future of the insurance industry holds.

1. What's the story behind Descartes Underwriting? Why and how did you begin?

TT: Catastrophe losses may double every decade due to growing demographics and climate change. So today, there is more need than ever for good Non-Life insurance covers. However, the Non-Life insurance sector is currently often not transparent, expensive and despite the urgency very slow at processing claims. My co-founders and I could not accept this status quo and started to look for better ways to cover the billions of losses a catastrophe or other natural hazards can leave behind. 

Our road quickly led us to new data sources. Normally, only a limited amount of data is utilized in the insurance sector, primarily applied for pricing purposes – so we tapped into this gap. We commenced using new technologies such as image recognition or machine learning combined with new data sources coming from satellites or the Internet of Things. Afterward, we started to apply our advanced data models to pricing & underwriting – making non-life insurance more transparent, faster and custom tailored. 

With the ambition to progressively reinvent the entire non-life insurance sector, Descartes Underwriting was founded in Paris, late 2018. Only 8 months later, we are today glad to have a core team of +10 people, to be backed by international risk carriers and financed by the largest independent European FinTech fund.

2. Please describe your use case and how Descartes Underwriting uses artificial intelligence:

TT: To make it short, there are three main use cases for AI in non-Life insurance: Distribution, underwriting & pricing, and claims management. Today, most of our efforts are focused on underwriting & pricing where we apply AI to improve our risk understanding and reduce friction costs caused by human interaction. We also work to a lesser extent on claim automation. Here, AI can enable us to assess the damage faster and thereby speed up claim payment. 

In general, the data we feed into AI is parametric, meaning that we use external parameters such as precipitation, wave height, and vegetation development to assess a claim and trigger a payment. For instance, we use satellite imagery to detect burned areas after a wildfire, find clouds responsible for hailstorms or evaluate water quality by identifying the spread of algae bloom. Since the quantity of data we process is immense, machine learning techniques and image recognition are crucial for us to be able to detect and analyze a wildfire, a specific cloud or an algae bloom efficiently. 

3. What are examples of companies/customers who benefit from your service? What has your company done for them?

TT:  Most of our clients are weather-sensitive. In other terms, these companies are vulnerable to natural catastrophes such as earthquakes, floods, storm surges, droughts, cyclones, wildfires or weather anomalies such as heat waves or excess of precipitations. Currently, we predominantly work with large corporations and governments through brokers. 

In contrast to many existing insurance partners, our approach has three advantages for our customers: Simplicity, accountability, and speed.

1) We ensure simplicity by minimizing the size of insurance contracts. In most cases, a one-pager is sufficient to describe any product appropriately.

2) We provide accountability by being 100 percent data-driven. Our parametric data approach does not only eliminate some transactional friction costs but also enables the utilization of smart contracts that leverage self-enforcing policies.

3) We are extremely fast compared to other industry players. In some cases, we even manage to trigger a claim's payment within a few hours after the insured event. Swift payout is key when dealing with natural damages since companies might face higher losses or bankruptcy without it. 

4. What other AI use cases in Insurance are you excited about?

TT:  AI will play a significant role in improving the insurance sector. We expect that all links of the insurance value chain will be impacted, however, we strongly trust that the effect will be greatest in the areas with frequent human interaction. 

For instance, in life insurance, agents and brokers can benefit from AI-powered personal assistants to better meet their clients' needs and boost productivity. Another exciting application is related to fraud detection since the insurance sector is plagued with suspicious and fake claims. Here, AI could help identify fraud more effectively by linking different data points e.g. spotting that the same phone number has been used for two different claim notifications. These are factors that today may go unnoticed even by the best fraud specialists. 

In the long term, AI will integrate the entire insurance value chain. It can help improve user satisfaction by leveraging enhanced risk assessment, custom-tailored policies, and effective and fast claim management. However – which is also crucial – AI will also ensure seamless customer experiences by forward and backward integration of the supply chain, for instance by not only securing clients financially but also assisting property repair, etc. 

5. Where will your company be in 5 years? 

TT:  We are currently living in a complex and challenging era. In the face of climate change and digitization, insurers will be forced to reinvent their business models to match the fast-paced development of our time. In this context, leveraging new data sources and AI techniques will be key and we aspire to be pioneers in this space.

Therefore, we have set three ambitious goals for Descartes Underwriting's future in the next five years:

1) We want to become a market leader in parametric insurance and remote sensing technology in the sector.

2) It is crucial for us to become the preferred partner of our clients, which entails innovating and ensuring a match with our customer's needs.

3) Reach USD 100M premiums across the world through a strong and diversified international team.

About Sam Mire

Sam is a Market Research Analyst at Disruptor Daily. He's a trained journalist with experience in the field of disruptive technology. He’s versed in the impact that blockchain technology is having on industries of today, from healthcare to cannabis. He’s written extensively on the individuals and companies shaping the future of tech, working directly with many of them to advance their vision. Sam is known for writing work that brings value to industry professionals and the generally curious – as well as an occasional smile to the face.