Artificial intelligence (AI) is a rapidly growing and evolving field that has many exciting developments and applications. Some of the current trends and advancements in AI today which is a hot topic is ChatGPT. As technology continues to advance, we can expect to see even more innovative and impactful uses of AI in the future. Gabe Minton of Mortgage connect sat with me to discuss AI and its accountability and how it will be useful in the mortgage industry.
Artificial Intelligence with Gabe Minton of Mortgage Connect.
I’m excited to have Gabe Minton joining us today. He serves as Mortgage Connects Chief Information Officer and Executive Vice President of Information Technology.
He has got an extensive background in this area and has served and provided leadership for many companies and provided vision for technology information strategy throughout the industry, including the development of the next-generation digital platforms to facilitate seamless experience between the consumer and the client and to maximize operational efficiencies. That’s one of my hot buttons and we’re going to get into that a little bit in this interview.
Gabe also has over 25 years of leadership roles inside of mortgage companies and technology companies, with a special focus on developing software systems and products, and strategies. Throughout his career, he has led strategy and execution, communications, and vendor relationships. Most recently, he served as a Chief Information Officer at Guild Mortgage, where he led its technology and information strategy, including business systems, architecture infrastructure,
Product and services technology. Also, Gabe has served in senior management strategy and technology positions at Black Knight Service Link, Motivity Solutions, Accenture Mortgage, Cadence, and the Mortgage Bankers Association. He has also been a leading architect and founding member of MISMO, the Mortgage Industry Standard Maintenance Organization, a subsidiary of MBA. He has earned a Bachelor of Science with a double major in Computer Science and Statistics and a minor in Mathematics from Radford University in Virginia, and a Master’s of Software Engineering degree from the University of Maryland.
Man, what an impressive background, here we go.
Gabe Minton so good to have you back on the podcast with me. It’s been a little too long.
Hey, it’s great to be here, Dave.
We’re excited about that. Now, you heard me just give a little bit about your background. I’d like to have you add about it. Most importantly, probably share with us what you’re most passionate about over the things you’ve done throughout your career.
Sure. I started working for the US Navy as a software engineer, and computer scientist. So, I bring an engineering sort of background to my career, and I’ve come up over the years and got into the mortgage and never looked back. And have held many, a variety of roles from technologists to working at the Mortgage Bankers Association, as you’ve mentioned to working at lenders’ shops to working at service providers. Currently, I work at Mortgage Connect, which is a national service provider to the mortgage industry. So, I’ve seen all sides of the table around mortgage, if you will. Similar a lot to you, except you have a lot more experience than even I have. With all the things that you’ve done. And I look to you as an example of that as well. I would say one, am I most passionate? I love solving problems and I also love working with people. So the mortgage industry is very small. We’ve known each other for a long time, so I like the familiar faces. And then working together to solve problems at an industry level, at a company level, at a lender level, whatever it might be.
Yeah. And you are one heck of a problem solver. Not only that, I love the Six Working Geniuses. We don’t have time to get into that, but one of the things he talks about is wonder and invention. And you are just always wondering how we could improve this industry. And you’re talking about inventing new things and you certainly have been on the cutting edge of many things that have been we’ve thought about accomplishing. I’ll never forget one dinner we had in Washington DC, where we sat around and we solved all the problems. And what’s so interesting about that dinner is the forward thinking that you had and others that were sitting around the table, it actually addressed a lot of the things and a lot of things got implemented that are very similar around what we discussed. So you’re clearly a thought leader and I’m really excited about getting into the topic today, which is artificial intelligence. So, listeners go back and listen to the previous podcast that I did with Gabe. This was back done way back in 2019. So, you’ll think we could have recorded it yesterday. There’s that much current information, but I think it’d be good, Gabe, for those that are not going to go back to that podcast, they should. But help us define AI relative to RPA and ML machine learning, and then robotic process automation. Yeah. Let’s think as an engineering automation. All right. So get, walk us through that.
Sure. Yeah. So I think of them as. And I do encourage everyone to go listen to that podcast. That was a lot of fun working on with you as well. But just to boil it into a nutshell, I’m very practical about using these technologies in the mortgage space to solve problems. And we’ll probably get into some of those examples a little bit later in the conversation, but I like to think of them as building off of each other. So robotics process automation is where it all starts, and this is if you have a rote. The process that you repeatedly do all the time, and it’s a human being that’s doing this.
I go to this website, I go find this file in this directory, and I put it in this directory on this laptop, and I do this every hour on the hour. And if you have a very repeatable, very finite defined process, that’s a great thing that you can use Robotic process automation around is doing rote repeatable tasks. Now if you do the road repeatable task over and over and over and over again and maybe use fuzzy logic, then you start to get into machine learning. Which is moving you towards artificial intelligence.
Explain fuzzy logic a little bit. If you could expand on the fuzzy logic when I understand RPA from the standpoint, it is very defined, exact. You put in this, you want this, but then you’re talking about fuzziness. Is it in the definition of the answer or how would you describe that?
Yeah, so fuzzy logic oftentimes, and you and I have brought up examples of assembly lines. Yes, in the mortgage space, I’m also talking, I remember talking to Doug Duncan about this at length, and you could be assembling a car, or you could be assembling a jet. So imagine if you’re assembling a car and you’re using robots to assemble the car. They do this. This is all real. And when they put the frame of the car together, the robot has to put the nut in the right part of the right hole to put the frame together. It has to be exact millimeters to get the threading to work.