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.
Digital financial services are becoming an increasingly common part of everyday life, with users expecting convenient and increasingly autonomous ways to manage their finances. However, mortgage financing remains a complex and highly individual process, while AI integration introduces additional challenges around trust, transparency, and user control.
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.
