Robo-Advisors in Real Estate Finance: A Comprehensive Study of Borrower Preferences and Platform Performance

The intersection of real estate finance, technology, and user preferences forms the backdrop of this comprehensive thesis. In an era where mortgage decisions and financial advisory services are increasingly shaped by technological advancements, this research delves deep into the intricate web of economic and psychological factors influencing borrowers' choices. The study navigates the evolving landscape of robo-advisory services, seeking to understand their role in the mortgage selection process. A meticulously designed survey captures the diverse voices of mortgage seekers, probing their views on economic factors such as cost savings, tailored financial solutions, and data-driven insights. Simultaneously, the survey unravels the enigma of psychological factors, exploring the significance of confidence, reduced stress, and independence in robo-advisor adoption. Statistical analyses and correlation studies breathe life into the data, revealing nuanced patterns and interplays between these factors. The findings not only shed light on borrower behavior but also offer practical insights for industry stakeholders. Through a comparative analysis of Better Mortgage, Rocket Mortgage, and Zillow, this research uncovers the strengths and areas for improvement in the realm of robo-advisory services. In conclusion, this thesis advances our understanding of the complex dynamics that underpin the mortgage selection process in the digital age. It proposes recommendations for robo-advisory platforms, envisions a user-centric future in real estate finance, and invites further exploration into the evolving landscape of financial technology. As the real estate finance landscape continues its transformation, this research serves as a compass, guiding industry players toward innovation, customer-centricity, and informed decision-making.