Informatica World 2024 | Jason Lindauer | Dun & Bradstreet, James Sizemore & Levent Ergin | Informatica

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Jason Lindauer

Senior Director, Global Head of ESG Products

Dun & Bradstreet

James Sizemore

Chief Strategist, Insurance

Informatica

Levent Ergin

Global Chief ESG Sustainability Strategist & Global Head of ESG Strategic Alliance Partnerships

Informatica

Harnessing climate risk insights: Informatica’s IDMC ‘s impact on ESG sustainability and insurance

Since climate change and global warming are wreaking havoc, exposure to climate risk insights is vital because it helps in the right course of action. As a result, Informatica Intelligent Data Management Cloud acts as a stepping stone toward providing visibility into climate-related risks, as well as offering insights about environmental, social and governance disclosures, according to Levent Ergin (pictured, right), global chief ESG sustainability strategist and global head of ESG strategic alliance partnerships at Informatica Inc.Informatica’s James Sizemore and Levent Ergin, as well as Dun & Bradstreet’s Jason Lindauer talk to theCUBE about the importance of climate risk insights

play_circle_outline Using Data and AI to Address Climate Change Challenges and Assess Resilience of Companies

play_circle_outline Leveraging climate risk insights for innovation and opportunity

play_circle_outline Maximizing Insurance Efficiency: Harnessing AI and Big Data to Predict Extreme Weather and Climate Events

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Jason Lindauer | Dun & Bradstreet, James Sizemore & Levent Ergin | Informatica

Jason Lindauer

Senior Director, Global Head of ESG Products Dun & Bradstreet

James Sizemore

Chief Strategist, Insurance Informatica

Levent Ergin

Global Chief ESG Sustainability Strategist & Global Head of ESG Strategic Alliance Partnerships Informatica

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>> Hello and welcome back to Informatica World, live here from Las Vegas in 2024. We're wrapping the day up and we have such an interesting, interesting panel to go through with you guys because I think one of the biggest things going on that we can't get away from is really climate sustainability and how it's really having an impact. One of the funny things is at the root of that is a lot of data and how data gets used. And what a better conference to be at to understand that than here. So I want to welcome on board Jason Lindauer, who's the senior director global head of ESG products from Dun & Bradstreet. We have Levent Egren, who's Global Chief ESG Sustainability Strategist and Global Head of ESG Strategic Alliance Partnerships had Informatica. And we also have James Sizemore, who's the chief strategist, Insurance, for Informatica. Thanks for coming on on guys. And as we get the voice of here over us telling everybody that they're going to be going to a keynote really soon, I think one of the things that really we want to talk through here is how data really impacts ESG. And I think again, you're a customer using Informatica, gathering a lot of data to really help people understand what's going on from a climate change perspective, because especially in things like insurance, there's a lot of impact going on there.

>> Yeah, thanks for having me. Climate is a big data problem. I mean, the economy, the world needs to get rid of about 900 billion tons of carbon in the atmosphere to get below pre-industrial levels. So that's a huge amount. And you need big data, AI, to help achieve this problem. Also, companies are faced with threats from climate change around their supply chain, around their operations, as well as being able to comply with new regulations around climate change. You've seen the SEC enact new disclosures around climate change. The state of California, EU, other countries have followed different regulatory frameworks as well. ISSB, International Sustainability Standards Board, is one that's taken over from the task force for climate related financial disclosures. So all these are coming together from supply chain risks to risks from companies operations. We've seen NOAA has calculated that there's been more than $60 billion plus disasters over the past five years that have costed the economy and companies more than $100 billion in losses. So this is a huge amount and a problem that companies need to be aware of and figure out how to solve it.

>> Yeah, And I think, again, having been in the insurance, not on that side of things, but on the casualty not property side, when we used to have actuaries, and this is like 2000, so we would sit there with old AI, no gen AI at that point in time and things of this nature and trying to figure out and using ML, which was what old AI is I guess you could say, and trying to figure out, "Okay, what is the life expectancy of somebody and things of that nature?" How are you seeing, from an Informatica perspective, how people are changing and using different techniques now as they approach that?

>> Well, I would say this. To your point, ESG requirements are either in place or emerging in 191 countries globally. I think all of the G7, most of the G20, coming soon to a town near you, right? So from an insurance perspective, it is very much on the radar. And from Informatica's perspective, the insurance industry response to climate change is really our opportunity to help carriers sort of shore up their legacy data estates so that they can respond gamely, if you will, to climate change by offering modern insurance products to their customers fit for these times.

>> Yeah, I mean I look at it and I go, "I know with hurricanes in Florida, I think we were talking about the wildfires in California, there's more and more challenges from an insurance perspective as we go out and do this." And as you said, it's a big data problem. And how are people really looking at, again, trying to understand this and gather all that data to do that modeling and really get a better feel? Because it seems like big data is a big word. The more data doesn't necessarily mean better outcomes, because you have to get through it. You have to prep the data, you have to understand it, you're going to catalog it, have metadata, and be able to understand that entire scope. How does that really play?

>> Maybe I'll take it first and then I'll hand off to Levent. So what DMB has done is combined our world-class data hierarchy around companies with climate data really focus on the perils and timeframes that the regulators want companies to report on. And the bank regulators as well are requiring many of the largest banks to do climate stress testing. So we incorporate that climate data from historical risks to current risks, short-term forecasts, as well as long-term forecasts. And that basically complies with the regulator's needs to say, "You need to report on what your acute risks are, near-term risks like wildfires and floods, as well as chronic risks like sea level rise that are going to impact the company over the next 20 to 30 years." And we combine that with DMB's almost 300 million global corporate entities where we're able to identify risks at specific company location levels where we have a geo-location identified to any company. We can actuate what that risk is as well as understand what the resilience of that company is based on its risk profile. Do they pay their bills on time? Are they at risk for delinquency? Looking at what is the building structure. Is this building made of wood which is more apt to go down in flames from wildfires? Is it a 10-story building or one-story building that comes into play for flood risks as well? So all these things come together, we're able to say, "Okay, you have your climate risk for a particular location and how that applies to its supply chain as well as to the parent headquarters company." And then also applying what's the resilience of that entity to come up with an overall climate exposure.

>> And I guess I'll take it from where you left off, Jason. So certainly when we look at the ESG disclosures themselves, and you've alluded to this James, they all center around your climate risks. What we're really excited about is making this climate risk insights data available as part of Informatica's IDMC for ESG sustainability, where we can go even beyond use cases such as the ones that we've explained in insurance, where we can even see in a company's supply chain, which of the providers or suppliers are going to be facing one of those perils in the next 30 days so that you can actually prepare for that, whether it's sourcing from an alternate supplier so that you can continue producing your products, or to Jason's point, looking at a time horizon of 2050, the use cases that unlocks for businesses is really quite exciting and opens up a lot of innovation so that this doesn't just become something about risk, but it's also an opportunity to innovate.

>> Yeah, I love that. Can I jump in on that?

>> Absolutely.

>> First of all, there's some real practical application there. Levent, you talked about it. But for insurance at least, carriers who want to accurately price to peril. You want to match price to peril. This sort of foundation of this sort of data is intimately important to that exercise. Or carriers who, again, I mentioned earlier, want to offer modern insurance products. So if I'm a carrier and I want to offer building-specific sensor-based parametric insurance, what you fellas are talking about supports that. If I'm a carrier and I want to offer a digital platform where I can take real-time data and advanced analytics and then use that to provide sustainability services to my commercial lines customers, this is a direct application to that. So from a practical implementation perspective or applied ESG, I'm excited about what you fellas are talking about and I think it's going to be very beneficial to the insurance industry.

>> Yeah, I mean I could see it like you were saying, Levent, that going across for CPG and retail and others as well, I mean, not only just insurance, but to your point, my previous job, for unknown reasons, the company built the data center in the basement of the parking garage in an area called the Seaport District of Boston, which is all landfill and it floods regularly. So when you start to go in there, and I owned DR and business continuity, and when you started to look at it and go, "Hey, what's the risk of this flooding?" It floods once a year.

>> Oh, gosh.

>> And so how do you build it? Now, the PDUs and everything, the batteries were one floor up. Still in the parking garage, still below, and it was a weeping bathtub. Okay, what takes the powers, the pumps out of that? Okay, we had a generator, but it wasn't the life and safety generator. To your point, I mean, I think taking these all into account and bringing that data. So is Informatica going to actually provide that out through the cloud-based system so that people can actually apply that to their models, I guess you could say?

>> Yeah. So you gave lots of industry examples there, certainly. So as Informatica, we allow and enable our customers to manage their data in a single unified platform where we will then be enriching that data with climate risk insights from Dun & Bradstreet, to then be able to get all of these additional dimensions to enable them to have those scenarios where they can then figure out what is the right course of action that we need to take. And certainly in the insurance side, there's opportunities to then perhaps even offer premium discounts for those companies who have taken those mitigating actions to potentially make their homes more resilient to certain perils. I mean, there's so many different opportunities for innovation there.

>> And that aligns to the general rise of predict and prevent in the insurance industry, sort of a shift from the old detect and repair to now predict and prevent. So all of this aligns, I think, very well.

>> Yeah. And when you look ahead and how this all plays in, because again, everybody's talking gen AI, but this is really the underpinnings of being able to potentially help an insurance agent quickly understand, "Okay, these are the things that connect back based on the data. Here's the other things." It's almost a mixture of experts type of thing where it's AI and gen AI to get to human in the loop type bot stuff. Is that where you see this really going from an insurance perspective as well?

>> Well, I think generally from an insurance perspective, sure. Using AI for example, we see use cases already starting to develop to detect fraud all the way back to first notice of loss, essentially to streamline the claims process, turning the claims experience itself into a competitive advantage. So there's a lot of practical application for AI. And particularly I think in the world of ESG, but I would defer to you, fellows, for that.

>> Yeah, I mean, just to expand on your example there, imagine if you could actually predict when the claims are going to come in because you know where those extreme weather events are going to take place. So you could actually gear up your call centers to be able to cater for that. And that's just one example on the underwriting and insurance side, but then what about on the portfolio side of the house, right?

>> Yeah, that's a great point.

>> So what exposures do you have as an insurance company? I mean, and that resilience question really applies to every other industry vertical as well. Healthcare, life sciences, what does this mean for my hospitals? As a healthcare provider, for my provider network, who are the ones that are going to be hit? Do they have the resilience to be able to bounce back? And that's where we use DMB's firmographic data. So there's a lot that can be done with this capability.

>> Yeah. One additional point, I think just enhancing the ability to predict climate events can be greatly enhanced by the use of AI and big data. Right now, we can predict probably two to four weeks, but beyond that is just a guessing game. And the long-term models, even when you go out to 2050, 2100, we can see the trends, but AI, especially the generative AI, LLMs, and transformers, are going to help improve that predictability going out into the future.

>> Yeah. And I think we're going to need AI to predict the actual impact of AI on ESG as well. But we'll table that for another time because it's definitely when you start to look at the EU and some of the studies that they're doing over there about, I think they were saying that all of the AI right now is using the effective kilowatts of what Germany is outputting in a year, which is just absolutely craziness. But I think this is something we'll dig into further. I really appreciate you guys coming on board and helping me close out day two here at Informatica World. Thanks for being on board.

>> Thank you.

>> Appreciate it.

>> Thanks for having us.

>> Yeah. Yeah. And thank you for watching theCUBE here. We're the leader in tech news and analysis. Stay tuned for more on day 3 from Informatica World 2024.

Jason Lindauer | Dun & Bradstreet, James Sizemore & Levent Ergin | Informatica

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>> Hello and welcome back to Informatica World, live here from Las Vegas in 2024. We're wrapping the day up and we have such an interesting, interesting panel to go through with you guys because I think one of the biggest things going on that we can't get away from is really climate sustainability and how it's really having an impact. One of the funny things is at the root of that is a lot of data and how data gets used. And what a better conference to be at to understand that than here. So I want to welcome on board Jason Lindauer, who's the senior director global head of ESG products from Dun & Bradstreet. We have Levent Egren, who's Global Chief ESG Sustainability Strategist and Global Head of ESG Strategic Alliance Partnerships had Informatica. And we also have James Sizemore, who's the chief strategist, Insurance, for Informatica. Thanks for coming on on guys. And as we get the voice of here over us telling everybody that they're going to be going to a keynote really soon, I think one of the things that really we want to talk through here is how data really impacts ESG. And I think again, you're a customer using Informatica, gathering a lot of data to really help people understand what's going on from a climate change perspective, because especially in things like insurance, there's a lot of impact going on there.

>> Yeah, thanks for having me. Climate is a big data problem. I mean, the economy, the world needs to get rid of about 900 billion tons of carbon in the atmosphere to get below pre-industrial levels. So that's a huge amount. And you need big data, AI, to help achieve this problem. Also, companies are faced with threats from climate change around their supply chain, around their operations, as well as being able to comply with new regulations around climate change. You've seen the SEC enact new disclosures around climate change. The state of California, EU, other countries have followed different regulatory frameworks as well. ISSB, International Sustainability Standards Board, is one that's taken over from the task force for climate related financial disclosures. So all these are coming together from supply chain risks to risks from companies operations. We've seen NOAA has calculated that there's been more than $60 billion plus disasters over the past five years that have costed the economy and companies more than $100 billion in losses. So this is a huge amount and a problem that companies need to be aware of and figure out how to solve it.

>> Yeah, And I think, again, having been in the insurance, not on that side of things, but on the casualty not property side, when we used to have actuaries, and this is like 2000, so we would sit there with old AI, no gen AI at that point in time and things of this nature and trying to figure out and using ML, which was what old AI is I guess you could say, and trying to figure out, "Okay, what is the life expectancy of somebody and things of that nature?" How are you seeing, from an Informatica perspective, how people are changing and using different techniques now as they approach that?

>> Well, I would say this. To your point, ESG requirements are either in place or emerging in 191 countries globally. I think all of the G7, most of the G20, coming soon to a town near you, right? So from an insurance perspective, it is very much on the radar. And from Informatica's perspective, the insurance industry response to climate change is really our opportunity to help carriers sort of shore up their legacy data estates so that they can respond gamely, if you will, to climate change by offering modern insurance products to their customers fit for these times.

>> Yeah, I mean I look at it and I go, "I know with hurricanes in Florida, I think we were talking about the wildfires in California, there's more and more challenges from an insurance perspective as we go out and do this." And as you said, it's a big data problem. And how are people really looking at, again, trying to understand this and gather all that data to do that modeling and really get a better feel? Because it seems like big data is a big word. The more data doesn't necessarily mean better outcomes, because you have to get through it. You have to prep the data, you have to understand it, you're going to catalog it, have metadata, and be able to understand that entire scope. How does that really play?

>> Maybe I'll take it first and then I'll hand off to Levent. So what DMB has done is combined our world-class data hierarchy around companies with climate data really focus on the perils and timeframes that the regulators want companies to report on. And the bank regulators as well are requiring many of the largest banks to do climate stress testing. So we incorporate that climate data from historical risks to current risks, short-term forecasts, as well as long-term forecasts. And that basically complies with the regulator's needs to say, "You need to report on what your acute risks are, near-term risks like wildfires and floods, as well as chronic risks like sea level rise that are going to impact the company over the next 20 to 30 years." And we combine that with DMB's almost 300 million global corporate entities where we're able to identify risks at specific company location levels where we have a geo-location identified to any company. We can actuate what that risk is as well as understand what the resilience of that company is based on its risk profile. Do they pay their bills on time? Are they at risk for delinquency? Looking at what is the building structure. Is this building made of wood which is more apt to go down in flames from wildfires? Is it a 10-story building or one-story building that comes into play for flood risks as well? So all these things come together, we're able to say, "Okay, you have your climate risk for a particular location and how that applies to its supply chain as well as to the parent headquarters company." And then also applying what's the resilience of that entity to come up with an overall climate exposure.

>> And I guess I'll take it from where you left off, Jason. So certainly when we look at the ESG disclosures themselves, and you've alluded to this James, they all center around your climate risks. What we're really excited about is making this climate risk insights data available as part of Informatica's IDMC for ESG sustainability, where we can go even beyond use cases such as the ones that we've explained in insurance, where we can even see in a company's supply chain, which of the providers or suppliers are going to be facing one of those perils in the next 30 days so that you can actually prepare for that, whether it's sourcing from an alternate supplier so that you can continue producing your products, or to Jason's point, looking at a time horizon of 2050, the use cases that unlocks for businesses is really quite exciting and opens up a lot of innovation so that this doesn't just become something about risk, but it's also an opportunity to innovate.

>> Yeah, I love that. Can I jump in on that?

>> Absolutely.

>> First of all, there's some real practical application there. Levent, you talked about it. But for insurance at least, carriers who want to accurately price to peril. You want to match price to peril. This sort of foundation of this sort of data is intimately important to that exercise. Or carriers who, again, I mentioned earlier, want to offer modern insurance products. So if I'm a carrier and I want to offer building-specific sensor-based parametric insurance, what you fellas are talking about supports that. If I'm a carrier and I want to offer a digital platform where I can take real-time data and advanced analytics and then use that to provide sustainability services to my commercial lines customers, this is a direct application to that. So from a practical implementation perspective or applied ESG, I'm excited about what you fellas are talking about and I think it's going to be very beneficial to the insurance industry.

>> Yeah, I mean I could see it like you were saying, Levent, that going across for CPG and retail and others as well, I mean, not only just insurance, but to your point, my previous job, for unknown reasons, the company built the data center in the basement of the parking garage in an area called the Seaport District of Boston, which is all landfill and it floods regularly. So when you start to go in there, and I owned DR and business continuity, and when you started to look at it and go, "Hey, what's the risk of this flooding?" It floods once a year.

>> Oh, gosh.

>> And so how do you build it? Now, the PDUs and everything, the batteries were one floor up. Still in the parking garage, still below, and it was a weeping bathtub. Okay, what takes the powers, the pumps out of that? Okay, we had a generator, but it wasn't the life and safety generator. To your point, I mean, I think taking these all into account and bringing that data. So is Informatica going to actually provide that out through the cloud-based system so that people can actually apply that to their models, I guess you could say?

>> Yeah. So you gave lots of industry examples there, certainly. So as Informatica, we allow and enable our customers to manage their data in a single unified platform where we will then be enriching that data with climate risk insights from Dun & Bradstreet, to then be able to get all of these additional dimensions to enable them to have those scenarios where they can then figure out what is the right course of action that we need to take. And certainly in the insurance side, there's opportunities to then perhaps even offer premium discounts for those companies who have taken those mitigating actions to potentially make their homes more resilient to certain perils. I mean, there's so many different opportunities for innovation there.

>> And that aligns to the general rise of predict and prevent in the insurance industry, sort of a shift from the old detect and repair to now predict and prevent. So all of this aligns, I think, very well.

>> Yeah. And when you look ahead and how this all plays in, because again, everybody's talking gen AI, but this is really the underpinnings of being able to potentially help an insurance agent quickly understand, "Okay, these are the things that connect back based on the data. Here's the other things." It's almost a mixture of experts type of thing where it's AI and gen AI to get to human in the loop type bot stuff. Is that where you see this really going from an insurance perspective as well?

>> Well, I think generally from an insurance perspective, sure. Using AI for example, we see use cases already starting to develop to detect fraud all the way back to first notice of loss, essentially to streamline the claims process, turning the claims experience itself into a competitive advantage. So there's a lot of practical application for AI. And particularly I think in the world of ESG, but I would defer to you, fellows, for that.

>> Yeah, I mean, just to expand on your example there, imagine if you could actually predict when the claims are going to come in because you know where those extreme weather events are going to take place. So you could actually gear up your call centers to be able to cater for that. And that's just one example on the underwriting and insurance side, but then what about on the portfolio side of the house, right?

>> Yeah, that's a great point.

>> So what exposures do you have as an insurance company? I mean, and that resilience question really applies to every other industry vertical as well. Healthcare, life sciences, what does this mean for my hospitals? As a healthcare provider, for my provider network, who are the ones that are going to be hit? Do they have the resilience to be able to bounce back? And that's where we use DMB's firmographic data. So there's a lot that can be done with this capability.

>> Yeah. One additional point, I think just enhancing the ability to predict climate events can be greatly enhanced by the use of AI and big data. Right now, we can predict probably two to four weeks, but beyond that is just a guessing game. And the long-term models, even when you go out to 2050, 2100, we can see the trends, but AI, especially the generative AI, LLMs, and transformers, are going to help improve that predictability going out into the future.

>> Yeah. And I think we're going to need AI to predict the actual impact of AI on ESG as well. But we'll table that for another time because it's definitely when you start to look at the EU and some of the studies that they're doing over there about, I think they were saying that all of the AI right now is using the effective kilowatts of what Germany is outputting in a year, which is just absolutely craziness. But I think this is something we'll dig into further. I really appreciate you guys coming on board and helping me close out day two here at Informatica World. Thanks for being on board.

>> Thank you.

>> Appreciate it.

>> Thanks for having us.

>> Yeah. Yeah. And thank you for watching theCUBE here. We're the leader in tech news and analysis. Stay tuned for more on day 3 from Informatica World 2024.