Optimal Blue’s Joe Tyrrell on deciding where to use gen AI

Editor-in-chief Sarah Wheeler sat down Optimal Blue CEO Joe Tyrrell talks about how the company decides where to deploy generative AI and why return on investment (ROI) for customers is critical.

Before arriving at Optimal Blue this year, Tyrrell was president of ICE mortgage technology and as Chief Operating Officer at Ellie Mae. This interview has been condensed for length and clarity.

Sarah Wheeler: What sets your technology apart?

Joe Tyrrell: There are three things that drive all our technical decisions. Most importantly, does it improve our customers’ ROI? We have these incredible solutions, in some cases with hundreds of capabilities that the customer can access.

If they only use twelve or thirteen, we’re not maximizing their ROI. How can we help the lender get the highest return on its dollars? We want to become more than just a supplier; we want to become a partner in their company.

Second, we never want to automate a bad process. We want to solve a problem, not just automate it. Third, ensure that any use of gen AI makes things better, not worse. We see lenders making big investments in gen AI, but when we ask what problems they solve, they don’t have a clear answer.

As a former Chief Credit and Risk Officer, I understand the consequences of introducing unintentional bias and how an error persists over the life of a loan. So even if a lender thinks an AI use case is cool, everything stops if the compliance team or operations staff become concerned. Generation AI allows us to articulate the specific problems we solve.

Wheeler: How does your background in lending – and lending technology – shape what you do now?

Tyrrell: I was a lender. I managed production and operations. I was an insurer. I ran a lock agency. I have done all aspects of the roles that our technology supports. I know what a lot of loan officers do: they know two or three programs really well, and they start using them and then they stop.

But what if loan program #21 offers a better rate or payments? We can put a generational AI assistant there to work with the originators, to offer all the qualifying programs and tell them that if borrowers improve 10 points with this program, there will be a lower payment – on one screen.

You can never build technology in a vacuum. At Optimal Blue, we will never use the product we built, so we talk to the people who do and involve them early in our process.

Wheeler: What else are you doing with gen AI?

Tyrrell: A lot of! We are the one and only secondary market platform with PPE on the front end, compliance, and then hedging and trading – no one else has all three. So we’re looking at all these personas. If you look at the back end, hedging and trading, lenders get all their revenue. They no longer charge 2 or 3 points to consumers, so this is where the money is made: it’s made in the secondary market.

How does Optimal Blue help them increase their profitability? We started with a profitability assistant. Every day, executives in the capital markets look: what have I lost or gained on turnover? To do that, they may need to open four spreadsheets and pull data from their system. Some executives can do it in twenty minutes, for others it takes two hours. This is a perfect use case for generative AI and is already available.

The profitability assistant sees all the data, knows all the data and calculates the profit or loss. Then you can ask it a question about the data: how it compares to yesterday or three months ago, and it can show you right away – and then remember what you asked for and add it automatically the next day. We’ve just saved you twenty minutes or three or four hours at the start of your day so you can take action and make an impact.

Originators are on the other end of the spectrum, but generation AI can show them the fifteen loan programs, show them where they do or don’t qualify for better rates, and what it will take to get there. This is currently being tested and we have more AI assistants that we will release at our user conference in February.

Wheeler: What is the ultimate goal?

Tyrrell: Our goal is to give lenders the ability to say yes to selling profitable loans. That requires a lot of unpacking, and it also has to be priced competitively, which depends on each company’s costs and rollover rate.

We are unique in that from the very first time an originator wants to price a loan, we can tell that company in real time with the borrower your LO is working with what the likelihood is that that loan will go through. We have all this data. It could be based on DTI, location, age, if they are first time homebuyers, etc.

And if you know that repayment of that loan is more likely than average, you can price that loan differently in real time. If you think there is a higher propensity to close, instead of a standard rate schedule, you can set a slightly lower price so they don’t shop around. If you did that and locked them up, you can make plans to sell that loan 60 days in advance. Most businesses are on the verge of closing; we operate at the point of thought to execution in the capital market.

Our AIa tools are focused on the back-end and front-end because if you get the front-end and back-end comfortable with AI, it’s much easier from a trust and adoption perspective. Then you get buy-in from the company and you can solve problems during the term of the loan.

Wheeler: What are some of the changes you’ve seen in technology over the past 18 months?

Tyrrell: This time last year I was CEO of a company called Medaland we worked with major global companies using technology for customer experience platforms. I learned so much in that year and a half, including understanding who the key stakeholders were. In the mortgage industry, if you solve problems on the front end and the back end, they become the masters within the company.

The other thing that has changed is the evolution of large language models (LLMs). When gen AI first came out, some companies were terrified of using it. Do I train public models for my competitors? Now LLMs have come so far and lenders have so many options.

The other thing with technology is that lenders are going through a period of very difficult times, where everything they do comes with new costs. Optimal Blue takes the opposite approach. All generation AI, machine learning, all automation: it costs no extra. If we really want to grow customer ROI, we must commit to giving them more value at no cost.

This is an advantage we have because we are backed by a company that does not make earnings calls. This allows us to invest and deliver value and not worry about a monetization strategy. Our monetization strategy is retention and delivering value to our customers.