Devin Daly of TRUE: How AI Can End the Cycle of Hiring and Firing
MBA NewsLink interviewed Devin Daly, Chief Revenue Officer with TRUE. As CRO, he is responsible for the firm’s revenue strategy and execution, including managing both the sales and partner organizations, in addition to business development and sales operations functions.
Daly has extensive experience within the mortgage and lending industry. He has held senior business development and leadership roles at Homebridge Financial, Vantage, and Ellie Mae, and is also a member of the New Jersey Mortgage Bankers Association. Devin holds an M.S. Degree in Computer Science from Kean University and a B.A. in English from The College of New Jersey.
MBA NewsLink: Volumes in the mortgage industry are inherently cyclical. Can technology really provide a solution to that?
Volumes in home buying follow well-established annual patterns, amplified or reduced by many factors including the economy, inflation and interest rates. We see that in the varying peaks and valleys of any chart of mortgage originations over time. Each peak represents a burden of work, each valley a lack of operational efficiency.
Technology can’t end volume cycles, but it can smooth out the impact. Lenders are using artificial intelligence, or AI, to achieve data automation in critical areas such as documents-to-data conversion and multiple stages of verification and quality control (QC). Provably accurate data, produced automatically, provides a foundation of “lending intelligence” that supports an elastic business model where staffing and workload is much less influenced by volumes.
NewsLink: You talk about data automation as a solution. How is that different from lending automation, such as LOS or RPA?
The lending automation promised by loan origination systems failed to materialize because the data they run on isn’t sufficiently accurate or complete. Extracting and verifying borrower data is stuck in the slow lane of manual tasks, with multiple stages of QC throughout origination needed to root out errors. Robotic process automation, without data automation, only serves to make error-prone decisions faster.
All that changes when docs-to-data conversion and data verification is automated using AI. The accuracy of these solutions easily surpasses 95 percent, paving the way for genuinely automated originations. Rather than replacing the LOS, the lending intelligence platform supplies quality data that enables lending automation to finally become a reality.
NewsLink: What innovations does TRUE offer that enable lenders to achieve data automation?
TRUE was born out of an AI lab. We have a heritage and many unique capabilities in machine learning technology designed to recognize and read documents. Applying this to the TRUE AI Platform, we trained it using the documents lenders routinely handle: bank statements, paystubs, W-2 earning and tax statements, personal identification, property appraisals, and more.
The resulting AI is unique to mortgage lending and we believe it’s the most accurate available. Intelligence is worth nothing if it’s not accurate, so, without getting too technical, I’ll just say that we train our machine learning models using real borrower documents. This focus and specificity allows us to outperform the accuracy not only of people but also comparable technologies from firms including Google or Amazon.
NewsLink: How will this technology affect employment in lending businesses?
There’s been a lot of talk in the media about AI stealing jobs, but we don’t see that happening for our category of AI in lending. Many lenders made layoffs due to the impact that interest rates had on volume, so the question now is when will volumes increase and how should the industry adapt to that.
Lending intelligence holds the key to a smooth transition. The AI does the heavy lifting with documents, data processing and data validation, allowing lending professionals to be more productive by focusing on more meaningful, high-value tasks such as exceptions and customer experience.
NewsLink: Does this really mean an end to the hiring and firing cycle?
I truly believe that’s the prospect for mortgage operations. I’ve seen great mortgage operators struggle trying to hire fast enough to keep up with demand and conversely, suffer in the process of laying off employees they value.
Although lenders will always have some need to vary staffing, lending intelligence decouples the link between loan volumes and staffing levels. This decoupling means greater job stability, based on higher productivity and operational elasticity and less volatility in personnel needs as volumes fluctuate. Combine this decoupling with the reduced risk that comes from more accurate and complete loans, and it makes for a more stable industry all round.
(Views expressed in this article do not necessarily reflect policy of the Mortgage Bankers Association, nor do they connote an MBA endorsement of a specific company, product or service. MBA NewsLink welcomes your submissions. Inquiries can be sent to NewsLink Editor Michael Tucker at mtucker@mba.org or Editorial Manager Anneliese Mahoney at amahoney@mba.org.)
