How a Serial CDAO Scales AI in Insurance with Verisk

**Louis DiModugno** (0:00)
The more data that you bring to the equation, the more elements that you have in the algorithm, the higher level of accuracy you should be able to reach with your outcomes.

**Cindi Howson** (0:20)
Hi, I'm Cindi Howson, host of The Data Chief. If you've heard me talk about data and AI before, you know that I believe everyone, not just data teams, should be able to get the insights they trust. That's why I'm proud to say that ThoughtSpot sponsors this podcast. ThoughtSpot's agentic analytics platform lets you simply ask a question in natural language and get clear, governed answers right when you need them. No fuss, no waiting. It's why companies like Cisco, Lyft, Hyatt, and Roche count on ThoughtSpot. See what the future of analytics feels like at thoughtspot.com.
Welcome to The Data Chief. I'm your host, Cindi Howson. Today, we're joined by Louis DiModugno, Global Chief Data Officer at Verisk, the number one data provider for all things insurance and the leading strategic analytics partner to the global insurance industry. Louis is one of those serial CDAOs with leadership positions at organizations such as Hartford Steam Boiler, The Hartford, and Axa Us. In this episode, we'll explore how to build AI-ready foundations, the growing role of unstructured data in decision-making, and why leaders must design systems that keep humans in the loop. Louis, welcome to The Data Chief.

**Louis DiModugno** (2:02)
Thank you so much, Cindi, for having me today.

**Cindi Howson** (2:04)
Yeah, and where in the world are you joining us from today, Louis?

**Louis DiModugno** (2:08)
So, I'm just outside of Snowy Hartford in South Windsor, Connecticut.

**Cindi Howson** (2:13)
Okay. How many inches did you guys get?

**Louis DiModugno** (2:16)
I think we got about 18 inches here.

**Cindi Howson** (2:17)
Oh, gosh. It's incredible. There's like no place to put it. Hopefully, by the time we air this, everyone will be in spring mode. And for those of you watching us on YouTube, Louis, the easiest way to spot you at a conference is the iconic bow tie. Share with us.

**Louis DiModugno** (2:37)
Definitely. So, I became the bow tie data guy when I hung up my Air Force uniform. And so, being in the Air Force and the military, obviously, it's very easy to know what you're going to wear day in and day out. And so, when I came over to the commercial side, I adopted the bow tie as my signature and it became my everyday currents. And I did an inventory around Christmas time. I think I have 227 bow ties now. So, my challenge to everyone is, if you ever see me with the same bow tie twice, I owe you a coffee.

**Cindi Howson** (3:16)
Oh, there you go. Well, it definitely is a classy look. And I should say, thank you for serving. Now, you mentioned serving in the Air Force, but you were actually a retired colonel. Is that right?

**Louis DiModugno** (3:31)
That is correct. I had 27 years total federal time, 12 years active duty, living all over the world, and then 15 years as a reservist, which really took me into some really unique areas. I had the opportunity of working at the Pentagon and was deployed from there to a number of initiatives that needed specific process improvement capability.

**Cindi Howson** (4:02)
I'm thinking about going from being a colonel in the Air Force, high pressure. I'm going to assume at one point you were looking after 22,000 aircraft, so a lot of data. But going from that to heads of data, give me the connection or disconnection here.

**Louis DiModugno** (4:28)
I have to say, in preparing for our discussion today, I went back and I started really looking at the connectivity between my military service and where I am now in the data world. One of the things that really resonated with me in doing that review is looking at the Air Force's core values and the core values, the three core values of the Air Force really align so nicely with what I do in data every single day. The three core values of the Air Force are integrity first, which again is a big piece of we need to make sure that we've got very accurate and high-quality data, service before self, and again, we are really focused on the aspect of what are we doing with that data and being able to use it to make informed decisions, and then excellence in all we do. That component of really continually trying to improve the data, improve the level of accuracy, improve the level of quality, it influences so much of the competence associated with the outcomes of the data. Again, those core values of the Air Force, I think just very much align with being a data professional, being someone who focuses on data and the foundation of our decision-making capabilities throughout the organizations. I think those core values really align nicely. I think it's probably a big reason why I am in the data space today. I did focus for a while on data science and the statistics side of the equation, but I found that the preparation and really getting the information ready for data science, there's just so much opportunities for efficiency there.