Impact AI Global Parametric Flood Coverage with Subit Chakrabarti from Floodbase
The impact of AI knows no bounds. Today, I am joined by Subit Chakrabarti, Vice President of Technology at Floodbase, a mission-driven, machine-learning-powered company specializing in flood monitoring and insurance. Having grown up in Eastern India, he knows the importance of adapting to global flood risk first-hand.
In this episode, Subit shares insights on how Floodbase utilizes advanced AI and diverse satellite imagery to support the design of parametric flood insurance solutions. We discover how machine learning plays a crucial role in analyzing vast datasets and bridging the insurance gap for regions vulnerable to flooding. Join us as we explore the transformative potential of Floodbase's technology and its vision for a more secure and equitable future, in the context of global warming and the associated global flood risk.
Key Points:
- Introducing Subit Chakrabarti, Vice President of Technology at Floodbase.
- Subit's background: what led him to Floodbase.
- Insight into Floodbase and its focus on parametric flood insurance and disaster response.
- Subit explains parametric insurance.
- How Floodbase uses machine learning to design the index for parametric insurance.
- Their use of satellite imagery and other geospatial datasets in setting up their ML models.
- The challenges of working with such diverse data sets.
- What made it possible to build Floodbase's technology (spoiler alert: advanced AI).
- How Floodbase measures its impact.
- Subit’s advice for AI-powered startup leaders: address bias and build a skilled AI team.
- Floodbase’s three to five-year plan: make insurance more accessible.
Quotes:
“Adapting to global flood risk is something that is near and dear to my heart, having grown up in India and having seen a lot of damage from floods in Eastern India where I used to live.” — Subit Chakrabarti
“Parametric insurance pays out when a pre-agreed weather condition is made separate from the physical damage.” — Subit Chakrabarti
“What we use machine learning for is to design [the] index that the parametric insurance can be based on, and that is our proprietary AI technology.” — Subit Chakrabarti
“One of the most important challenges with satellite imagery is that satellite imagery represents the condition of a place at a certain point in time and it’s not the continuous movement of what that flood looks like at that place.” — Subit Chakrabarti
“Our policy at Floodbase is that we add more data to remove bias from the process.” — Subit Chakrabarti
“The biggest thing that we can measure is the flood protection gap. So like I said, 83% of losses are uninsured and we can measure that.” — Subit Chakrabarti
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