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MortgagePoint » Your Trusted Source for Mortgage Banking and Servicing News 48 June 2024 S P O N S O R E D C O N T E N T SERVICING TECH ROI CIRCA 2024 (INCLUDING AI) B y DAV I D D O Y L E T he U.S. mortgage industry is nothing if not competitive. The 2022 HMDA data shows 4,460 active lenders—most of which are characteristically persistent (or optimistic), refusing to exit the business despite historically brutal conditions (not exactly a "soft landing"). The result has been an imperative for true "competitive advantage," which can take many forms: innovation, quality, development of proprietary methods, even a relentless, "won't lose" culture. But cost leadership stands as the most effective advantage for any mortgage oper- ation because of the correlation between new loan manufacturing and servicing costs and the ability to compete effectively for new and returning customers. In short, cost advantage is pricing advantage. Every basis point matters in mortgage servicing. Fortunately, modern servicing technology can automate manual pro- cesses and use data and AI to save money across the entire loan lifecycle—all while delivering better experiences to your servicing teams and borrowers. By transforming servicing operations from largely manual to exception-based processes, servicers can have their teams hyper-focused on high-value customer interactions and exceptions, rather than time-consuming, routine tasks. Modern servicing platforms also keep servicers current and compliant without system overhauls as regulations, policies, and markets constantly change. Is it possible for servicers to operate at $180 to $200 servicing cost per loan, compared to the MBA industry average of $250? Let's take a look. How Real-Time Data & AI Transforms Servicing Operations A unified platform with cloud-na- tive architecture is the foundation for leveraging AI and Large Language Models (LLMs) in mortgage servicing. The promise of AI in mortgage servicing depends on single-source, real-time data across the entire performing and nonper- forming lifecycle. Enter Dara AI | Docs—one of Dara by Sagent's first-to-market compo- nents—which transforms unstructured documents and extracts data (including stamps and signatures) to enable efficient loan movement for loan boarding at scale. Other use cases include digitizing income calculations with mortgage-spe- cific AI for salary income from W2s and paystubs, as well as automating claim filing utilizing extracted invoice data for reconciliation. In a real client example, Dara AI | Docs saved an estimated 34,155 people hours in just one MSR bulk acquisition (over one hour per file). Dara AI | Docs also reduced the buyer's exposure to unrecovered corporate advances, identi- fying $6.3 million of corporate advances that were not recoverable due to missing invoices in the data file. Embracing Short-Term Discomfort for Long-Term Gains and Scalability W hile some servicers may hesitate to adopt new systems and solu- tions because of business disruption or aversion to change, the benefits of a truly modern servicing platform are clear and attainable. One simply needs a clear view of the cost benefits and a firm commit- ment to execute the change. Sagent created Dara to meet a press- ing and unmet demand: servicers have long needed a unified consumer and operator experience where all users can view the same real-time data at any point in the loan lifecycle. D A V I D D O Y L E leads Sagent's Sales and Business Development programs. He drives Sagent's efforts to engage with new customers and strategic partners, contributing to revenue growth and the modernization of Sagent's system. David joined Sagent in 2020 after a 24-year career at Bank of America where he led several business divisions and large, transformative programs in the Consumer Lending space (mortgage, home equity, and auto lending). His background and experiences leading marketing, sales, operations, and support functions gave him a diverse skill set for business-to-business and business-to-consumer leadership roles.