[David] Mr. Pollack. So good to have you here with the Tech Update. You always are the caboose in this, but we can sometimes say the best for last ’cause I was talking to Michael Brady over the weekend, or it’s actually Friday. He had a great conversation with him. He’s the CIO, Allen at LeaderOne. A guy I really respect and a lot. And he’s talking about all the technology. He has a goal of having 150 AI agents working in the background, just continuing to pick up increasing productivity. It’s just, it’s really fascinating the effort that’s going in with a lot of lenders to take advantage of this thing that we hear every day AI. Give us your report.
[Allen] It’s interesting you brought that up. I was gonna get into some funny news, but before I do, there’s a website out there called. Is it worth the time.com? Is it worth the, and what you do is you, is it worth the time and you put in the salary? So I just, as an example, I just put in one 50 and you can view the data as money or time and how much did you save? And you can say per month or per year. So as an example, it gives you a chart and it shows that if you save one minute and you ran a bot 50 times a day, some automation, yeah, you’d save 1,300 per month. If you ran a bot only five times per day, instead of the 50, you’d save $651 per month. And if you ran that same bot just once a day, not 50 times a day or five times, you’d only save one 30 a month. And then you can get into all of these different. I’m at the website scenarios. This is an interesting website. Yeah, very cool. Check that out, listeners, if you’ve never seen it obviously it’s, it has a lot of ambiguity built into it, but yeah, of course you wanna just, make your brain think for a second. And that is a big question, David. I spoke with a large nationwide lender the CEO this weekend. And one of the things he told me was that you gotta spend money on ai, but there’s no savings yet. And that’s not the first person. Everybody’s saying the same thing, right? Where, what do you spend it on? And where’s the savings? And AI has a tendency to hallucinate and yes, just as an example, no matter how well or how fine tuned you do with ai, it will think of its own thing. Funny enough, there is stories of where Google AI and other ones have made up fake information. You tell it to go left, it goes right, but then goes left and says went right first. Here’s a funny story about AI. It’s called the ball headed incident. It’s an AI driven soccer cam, a Scottish soccer team installed an AI powered camera to track the ball. Automatically, the system kept mistaking the linesman bald head for the soccer ball continuously panning away from the action to focus on the guy’s head. That’s hilarious. I got a way to go on that. AI improvement. That’s fine, right? Kendall would be tracked a lot. Funny enough get this is just an interesting piece of news. David and you, bill would be tracked a lot. Yes. I’m trying for the folks that may be bald. I’m trying to divert the attention away. Yeah, so remember we all know Wikipedia well, January 15th, 2001. So we’re about 11 days beyond that, it had just a hundred pages. Today the free encyclopedia has become one of the most expansive collections of human knowledge. It has over 65 million articles across 300 plus languages that are viewed 15 billion times each month. How wild is that? That’s right. 300 plus languages. It’s viewed over 15 billion times each month, and it has 65 million articles. And it started, what date did I hear you correct? They had only 100 articles on January 15th, 2001. Wow. Talk about the proliferation of information. Yeah. And since we’re going off such great information, how about I give you a shower? Thought is a really good one. Okay. The more the world moves towards cashless economy, the harder it becomes for the average person to participate in money longer. Interesting. Yeah. You could think of instead of working out and thinking about all the other things you do, think about that next time. Yeah. Alright, let’s move on to some things going on in the mortgage industry. The first one is loan works. They’ve just embedded David, we speak of them all the time. AngelAI. So Loanworks just embedded Angel AI into their core mortgage workflow and they’re saying it’s a full integration meaning that AI is no longer a bolt on tool at the edges, but it’s embedded into everyday origination lifecycle and AI supports sales, fulfillment, communication, and compliance as it’s built-in operations infrastructure. Pretty cool there. Yes. We’ll see more of that and hear more of that. Nexa we all know who Nexa is. Nexa Lending just launched their advanced chat and social AI four LOS, so they unveiled what they’re calling their chat and social AI capabilities. Their own proprietary AI platform to act as a digital teammate for loan officers. So there’s a new word for us, all the digital teammate for loan officers. It features real-time investor pricing scans, intelligent loan structuring, automated responses, and AI powered social media content creation. Now what’s interesting is there are a lot of vendors or a number of vendors, I shouldn’t say a lot, that do a lot of those little things, right? So they probably were tired of trying and testing many other little ones out and decided just to take great own. Yeah. Yep. And you’re gonna see a lot of that. But with that being said, are seeing a lot of that. Yes. Yeah. With that being said, and I had something here I’ll say it real quick and then we’ll get back to the ai new res plans to allow crypto assets in their underwriting. By the way. For asset verification as of February of 26. So that’s pretty cool. But let’s get back to the ai. I know I just went a DD on you there for a second. Squirrel. Yeah, squirrel. The AI policy for lenders at Freddie Mac is still developing. I brought this up but I need to bring it up again for the folks that are actually tracking on this. So if you remember, they updated their sellers guide requiring formal AI governance. It goes into effect March 3rd. We’re getting closer and closer remains a backdrop to tech adoption. It includes the following folks, underwriting and credit decisions, income asset and employment validation, document classification, data extraction, pricing eligibility, prequel, borrower communications. If they influence decision servicing, default and loss mid decisioning. And that means that if AI is used in any of those places, you as the lender, you have to document and store you, you will be audited. It’s not optional. It’s mandatory. What AI is used, who owns it, how it’s monitored, how biased and fairness are assessed. That’s probably one of the hardest ones. How outputs can be explained and what happens when the model fails or it’s wrong. And even more. So if the AI comes from a third party vendor, it doesn’t matter. You still have to maintain all of this. And for those of you thinking why did Freddy just announce that? Don’t forget. FHFA has a lot of focus on AI. They have what they call a formal AI compliance plan, and they have an AI ML risk mitigation expectation document. So those documents can easily be found online, but FHFA is forcing everybody from the higher level based on all the governance around ai. So you could easily just go get a bunch of ai, you now your feet are being held to the fire. You have to understand what it does, and you have to be held accountable for its actions. Conversations are gonna shift a little bit, I think. In that area. And then obviously David, next week we’ll talk more. There’s one big topic that I brought up earlier, which is how to pay for ai. You’re paying for all these tools, the cost of loans not getting cheaper, so how do you pay for it?
[David] So true. It’s so true. And no one, even when someone, smart guys at Microsoft say, we haven’t figured out how to make any money with this AI that says something. So we have a whole lot. We are a laggard industry. We’re tracking, we’re the slowest to figure it out. Sometimes I’m not saying that well, industry.
[Allen] Maybe David, if you think about it, if everybody had to invest in ai, then maybe all the rates wouldn’t be as good because each lender would have to compensate, they’d have to adjust in order for the cost. So they couldn’t offer a great rate. But the reality is not everybody’s offering it. So if your rates increase. Because your margin is dropped. So you need to maintain some baseline margin, but not everyone’s investing. Then your rates aren’t as good as everyone else. So now are your originators invested in you? You may not have the best rates, but you have the best tools and the best way for them to make a living and you have the best service. We all know the answer to that, but not every ello thinks that way. But yeah, it’s an interesting conversation.
[David] Yeah, it is fascinating. There’s so much AI is just getting more and more attention. That’s what’s really interesting at CIS how much everything, it’s ai, everything. It’s just a complete, almost change it to an AI conference, but fascinating. Good stuff. Always love having you on. Always love the content. You always get us some new fresh ideas. Thanks for bringing up Loan Works. That’s one of my clients and I was instrumental in helping them get through that to them, make that decision. So they’re making a lot of noise about it and it getting a lot of decisioning. I mean it was getting a lot of attention is what I’m trying to say. Anyway. Good stuff, Allen. Thank you so much.
Allen Pollack
, Chief Operating Officer, Tech Consultant
Allen Pollack, a Mortgage & Financial Services Technology Advisor, is a subject matter expert in the mortgage origination process along with software product management and software development.
In today’s financial services push to all things Digital, Allen has been helping lenders and financial services solution providers align their digital transformation and technology strategies by removing the human element of risk, and automating processes that drive efficiencies and margins into profits.
Over the course of his career, Allen has co-created and developed technology business models that have birthed highly successful, innovative solutions and companies.
Allen co-founded and served as CTO of New York Loan Exchange (NYLX), a loan product eligibility and pricing engine (PPE) that made an immediate impact on the industry, scaling the company quickly and forming partnerships with multiple mortgage and financial lending companies. In 2012, Allen was a co-founder of a merger between NYLX and Aklero Risk Analytics that created LoanLogics, A Mortgage Loan Quality and Performance Analytics company. Allen served as CTO where he continued to bring new and innovative product solutions to the market that made a significant impact to mortgage lenders that reduced risk, scaled business channels, and grew profits in a very competitive and highly regulated market.
Allen is also is mortgage and finance technology contributor on a weekly live industry podcast, Lykken on Lending, and is launching a new podcast soon to be released, TechStack Radio, dedicated to technology and innovation in Financial Services.