CoreLogic's Pat Dodd on the company's transformation

August 27, 2024 5:00 AM

Approximately 10 months after CoreLogic went through a bruising hostile takeover battle that ended with it going private through an acquisition by Stone Point Capital and Insight Partners, then-CEO Frank Martell stepped down.

The company's board then promoted Patrick Dodd, first on an interim basis and then permanently in June 2022 as president and CEO. Dodd joined the company in late 2020 as its chief operating and growth officer.

Patrick Dodd is the president and CEO of CoreLogic.

While CoreLogic's end markets in insurance, real estate and mortgage are quite different from Nielsen, where Dodd worked previously, he noted that he has worked around data, technology and analytics for three decades.

Recently, National Mortgage News spoke with Dodd regarding what has been happening at CoreLogic since the company went private.

The following are portions of the conversation, edited for length and clarity.

On stepping in as president and CEO at CoreLogic

I came at a very interesting time... As I joke with people, I thought I was joining a public company [but] that lasted about 30 seconds, because quickly after my arrival, all that exciting stuff happened.

It was...I think a very good outcome for CoreLogic in the end. [Taking over as CEO] did allow me a really interesting perspective, to spend a lot of time with customers, talking to employees in my previous role. I did have some hypotheses when I came in about what CoreLogic's towering strengths were, where we needed to improve and see how we continue to transform the company.

I wasn't just dropped in with a blank piece of paper. I did have a year to make a lot of notes prior to them asking me to step in, which was truly helpful, if you think about it, because I got to spend a lot of time with the staff, a tremendous amount of time with clients across all the verticals we serve.

But the more I looked at what CoreLogic had accumulated over many years — even before it was owned by First American and then after — one of the things that amazed me about the company was just the client base that had been accumulated over that period of time.

On CoreLogic's next stage

One of the things that I'm very proud of the CoreLogic organization for, which might sound a little trite, is our empathy skills of listening and really understanding what our clients and our employees require from our company, which has been critical to our transformational efforts.

We really are trying to live by a philosophy that inputs drive outputs, and inputs being a highly engaged workforce across lots of different types of job families at CoreLogic. We're a B2B company.

A lot of people were wondering, should CoreLogic move into the B2C space? B2B is our play, so that was a very important decision for us, as opposed to maybe going into the portal wars or other parts of the ecosystem. But that simple filter is that we're here to help property professionals, anyone in the housing system, help their customers.

Those empathy skills of understanding our clients' problems and then working to bring the full power of CoreLogic to help them solve those, that's been quite critical to us.

On taking down internal silos

As in any good, scaled organization, silos do creep up, particularly because CoreLogic was built up of many acquisitions over time. I think the previous management team did a good job of integrating aspects of those companies, but not truly end-to-end. We've been on a very large culture and silo-busting effort internally.

As I've talked to a lot of clients out there. It was quite amazing that they said, "Pat, we don't understand what's inside of CoreLogic. We don't know if you're a tax and a flood company, or if you're a data and analytics company."

As much as previous management did a great job with the company, the awareness level of what CoreLogic has to offer to solve their problems is not all that well known. We did throw the organization up in the air, and it landed in a new structure.

Obviously data and technology is at the center of everything we're doing. We've been spending a lot of time internally on what I call our data strategy and our software strategy around that data. It's easier for our teams to consume it, but also for our clients to consume it as well. But this silo busting will continue. It takes some time.

CoreLogic has been around for a couple of decades now, and it's been built a certain way, but I'm quite pleased with the progress here, and it's starting to show up in our employee engagement results. It's starting to show up in our results with clients. Those are good signals that we're on the right track.

But this concept of "the client is the North Star" at CoreLogic ... some of the feedback that I was getting from the industry is as it relates to empathy and innovation, was that there was room for improvement, in terms of the vast data and technology that's sitting inside the CoreLogic ecosystem right now.

On the benefits of going from public to private

I think it was the perfect time for CoreLogic to be private. I do think it allows for a bit more speed of transformation, our ability to really take a sharp eye on things and say, "let's make decisions for the long term" and not have to justify them on a quarterly basis.

That's not to say that we have not kept all the mechanisms to be a public company again in place at CoreLogic, because we have. There is a board of directors. We still work on a quarterly cadence in many ways, but I'll give you two examples where I think we have been investing at record levels the last two or three years:

We had started our cloud migration a few years ago, moving all of our data repositories into the cloud environment. I'm happy to report, just in Q1 of this year, we've moved from 10,000 servers across all of CoreLogic in different parts of the country and worldwide, down to zero. We have been able to complete our full cloud migration of our entire data stack, which is quite extensive, if you think about what CoreLogic has: well over 22,000 data supply chains that come together in one repository, all the various pieces of software that we offer.

We've also acquired a handful of businesses in the last two years. We've acquired companies, but we've also rationalized a few parts of our businesses that we didn't think were core. That portfolio rationalization, I've always found you can speed up a little bit under private ownership as opposed to public.

But those are just two examples of about ten that I believe the benefit of being private has helped accelerate our timeline to get that work done. Obviously, given where interest rates jumped up in my first quarter of being CEO, given some of our business is sensitive to interest rates, being private in this environment [has been beneficial], compared to some of my public CEO colleagues that have to report on how the market is affecting their overall transactional side of their business.

CoreLogic is far less sensitive to interest rates, particularly in the data analytics world, serving lots of different property professionals. That's helped us really think about our business model a little bit differently as well.

On the source of product innovation

CoreLogic, before going private, had a lot of great attributes to it, and our customers reiterated to me how essential we are. But the one area that did come through, and I noticed it as well, is our product innovation probably was not at the highest level that it could have been, and we've been investing a lot in product development, not just acquiring companies and putting them into CoreLogic, but truly building products and services that meet the needs of our various end markets.

In the last two years, a big piece of it was centralizing and really making sure that our truth set — I call our data repository our truth set by the way, because when you take all of these disparate data sources and put them into one repository, and you eliminate bias — you take a lot of rigor and discipline to that data to make sure it could be trusted.

That's a great opportunity for any company, and it's not just data companies, but any company that really treats their data like an enterprise asset and cares for it that way. We've been spending a lot of time there because our clients depend on this data for really important decisions, and it needs to be high fidelity and high quality.

All of our information is in one spot now, all 22,000 data sources. When you think about connecting information, it's operationally more efficient, which is good for us. But actually turning this into a product development workbench is far more interesting to me, and thinking about how we drive analytics and our product leaders and our customers doing discovery work together to say, "how do we solve this problem and really tap into our platform to come up with new products?"

On the company’s image analytics tech

Image analytics has also been another key area for us, where we're collecting photographs from over 75% of the appraisers in the country on properties. We have a great relationship with all the MLSs, and you can imagine all the images that real estate agents put through their MLS listings, and we're also dealing with the majority of the contractors in the insurance segment that also take a lot of photographs.

Think of billions of photographs coming into the CoreLogic data repository, and us being able to build models and truly building content that can help property professionals.

That is an example of building new products that can really help people around appraisal modernization, if you put that into the origination workflow, helping appraisers get a few more homes done in a week. This is really about taking out cycle time, shortening that time using data analytics so they could really take care of their customers better.

On today's buzzword, artificial intelligence

Like a lot of good companies have, we've been leveraging what I would call traditional AI techniques for 15 years, be that OCR reading of documents, making sure that our data supply chains have the right robotics in it to check what I call the mundane and the routine. We have a million quality checks we go through.

That's AI at the end of the day: smart machines doing the mundane and the routine work that you'd have to throw a lot of bodies at in the past. We are sitting on what we call core AI enablers between the models that we've already built. We have over 200 at CoreLogic.

On the future of AI

We're doing a lot of discovery work and beta testing and prototyping about how to [use] responsibly, how to ensure that it's responsible AI, but also very cyber-secure. You know what's happening in our industry right now with information leaking out.

We schooled up two years ago a governance council around AI and Gen AI — because we saw this coming — to make sure that our product teams and our engineering teams are going to be building things properly. You do need some scale for this, in my view, to do it for the types of clients we deal with.

We want to be very practical, because you could do a lot of things with large language models. We are trying to go very deep with certain groups of clients and saying, what problems can we really solve?

Three of them that come to mind: One is with real estate agents and generating a listing and how much time that takes for a real estate agent to do it when they go back home. Just imagine being able to have two thirds of that filled in for you already, or maybe 90% of it, because we have all the property characteristics. We have image analytics. It can be translated into three languages with a push of a button, and you can collect that information now with just sweeping your phone inside the home that you just got listed. If you think about the time it takes to create a listing, even if it's 15 minutes, if we could shrink that cycle time down to two minutes for a high quality listing. The better the listing, the better your chances of a sale and eyeballs, that's an example where we're doing a lot of work right now with generative AI.

The second one would be around appraisers, the time it takes to go through a home and measure all the characteristics. There's many of them still on an iPad, or they might even still have a clipboard. You can imagine what we could do with [large language model] technology, talking into their phone. All the property characteristics are already listed in the document for them from CoreLogic data. They can spend less time doing administration and more time doing the high quality work that they're paid to be doing, as opposed to administration.

Even our own teams, we're looking at everything. Why do you have to look at four screens before you can come up with the right answer? How do we just give this to you on one screen and give you the answer you need, so those poor people don't have to be flipping through pages of material? Even having the content in one spot so they can eyeball it, that could take minutes off the mundane and the routine.