Concept and prototyping of a self-service platform for mortgage financing. Developed as part of my Bachelor’s thesis, from initial research and concept development to a high-fidelity prototype.
Concept and design of a self-service platform for mortgage financing, designed to help users navigate the early stages of the financing process independently. The goal was to help users understand their financing options, make informed decisions based on their individual situation, and confidently progress through the process - from providing their financial information to submitting their application for review.
Mortgage financing is a complex and highly individual process that often requires guidance, reassurance, and a clear understanding of what is happening at each step. Introducing AI into this process creates an additional challenge: how can users confidently navigate an increasingly automated experience without feeling like they are losing control over important financial decisions?
The challenge was to design an AI-supported mortgage experience that makes complex information easier to understand while giving users transparency, meaningful control, and confidence throughout the process.
I explored how users perceive fintech services and what they need to feel confident using them. The research combined desk research, hypothesis-driven empirical research based on the Technology Acceptance Model (TAM), and persona analysis. These methods helped identify user attitudes, expectations, and acceptance factors relevant to an AI-supported mortgage financing experience. Three key principles emerged from the research: trust, transparency, and user control.
These findings shaped the design approach and the integration of AI-supported functionality throughout the experience. I focused on creating a clear and understandable platform, with AI interactions designed to be predictable and transparent while giving users visibility and control over their decisions and data.
