Rapidio’s Michael Tuch: Hone Your Lending Operations to Reduce Origination Costs, Strengthen Profitability

Michael Tuch is the Co-Founder of Rapidio. Powered by its proprietary Al technology, Rapidio’s data platform provides lenders with accurate, reliable data extraction to improve data accuracy, reduce risk, streamline processes and help meet regulatory compliance requirements. 

Michael Tuch

Mortgage lenders are losing money on loans for the first time in years, reporting a net loss of $534 per mortgage origination in the second quarter of the year. Marking the fifth straight quarter that banks lost money on mortgages, there is a tremendous need to control costs and identify better processes.

Meanwhile, mortgage demand has recently fallen to the lowest level since 1995. It’s unclear when demand will normalize, but a survey from Wolters Kluwer shows that lenders are currently focused on identifying technology that will help them scale when the market returns. Among the 110 mortgage and financial executives surveyed, a clear majority (79%) say they will rely more on technology to scale operations, while less than one in 10 believe their company’s current technology resources will allow them to scale up or down based on the economy.

But rather than focusing solely on its ability to scale, lenders must use the current market to hone their lending operations and uncover greater efficiencies that drive stronger profitability and drive down origination costs long term. Even when demand throttles back up, lenders must have the ability to control costs at the loan level.

The key to balancing scalability and profitability? AI and a technology-component approach. 

A Component Tech Stack Is Critical

Lenders need greater flexibility with their technology if they plan to reduce costs and increase profitability. End-to-end systems are rigid, and often include services lenders may not need. For example, when a lender receives an income waiver, they must pay for an income assessment to get the asset, liabilities and credit assessment. That’s like paying for the entire buffet when all you want is a muffin.

Instead, lenders need a new type of technology infrastructure built using a microservices architecture that empowers them to utilize specific components when they need them. Not only does this eliminate costly and time-consuming integrations, but a modular design means lenders can assemble the high-performance components that suit their team, scenarios and current manufacturing process. A component approach also allows financial institutions to better understand the cost prior to underwriting to measure profitability.

AI Shouldn’t Be Feared

The use of AI has been controversial, especially amid repeated warnings from regulators and several consent orders related to fair lending compliance. In one recent case, the FDIC deemed the bank responsible for its use of AI, indicating heightened scrutiny of bank-fintech partnerships.

But this shouldn’t deter lenders from leveraging it. When safely adopted, AI can revolutionize mortgage lending by identifying patterns within documents, automating workflows and simplifying data extraction. However, this process must be clearly defined and transparent. In fact, regulators have explicitly stated that if AI makes a decision, there must be transparency for how those decisions are made to ensure they are fair and unbiased.

This means AI should be used in tandem with underwriters, not act as a replacement. With complete transparency and access, underwriters maintain authority and control to make decisions with confidence rather than relying on technology to make decisions. AI allows them to save time by cutting out tedious tasks, speed processes and ensure greater accuracy.

AI can also help reduce risk if used appropriately. Bad actors know which data fields are collected for mortgage underwriting and bank on limited data cross checks. Without the entire data story, fraud can slip through the cracks. Instead, lenders must have technology that ingests every data field from every document, even though it’s not required. With complete data, lenders can ensure comprehensive crosschecks and all but eliminate fraud. 

Positioning for Success, Today and The Future

In today’s mortgage lending landscape, where profitability is under pressure and market conditions fluctuate, it’s imperative for lenders to adapt and innovate. The recent challenges faced by the industry and the soaring cost to originate have highlighted the urgency of honing lending operations. While the cyclical nature of the mortgage market is nothing new, it underscores the need for proactive measures to control costs and enhance profitability.

The combination of AI and a component-based tech approach is the key to navigating the complexities, reducing costs, and ultimately strengthening profitability. Now is the time for lenders to embrace these transformative tools and position themselves for success today and in the future.

(Views expressed in this article do not necessarily reflect policies 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 Editor Michael Tucker or Editorial Manager Anneliese Mahoney.)