rent2own

Inspiration

The inspiration for rent2own comes from the growing struggle of people who can’t afford to buy a home, yet continue paying rent without ever building equity. We wanted a model where renting becomes a step toward ownership rather than a financial dead end.

What it does

rent2own enables renters to gradually acquire a small share of the property with every month of rent paid. Over time, they build partial ownership, which they can later cash out, reinvest, or keep to earn income from rental returns - transforming rent into long-term financial benefit.

How we built it

Started with a basic website skeleton
Created modular React components
Combined everything and made it pretty :)

Challenges we ran into

The most challenging part was developing the financial model behind rent2own. We had to figure out whether the concept could realistically work, run concrete numerical examples, and experiment with many parameters (ownership percentages, payout scenarios, rental yields, etc.). Finding a model that is both fair and actually feasible in the real world required multiple iterations and careful calculations.

Accomplishments that we're proud of

We developed a completely new and revolutionary housing concept that is not only innovative, but also financially feasible in the real world. While traditional profit-driven investors may not adopt it, socially oriented institutions like Studentenwerke could realistically implement it. On top of the concept itself, we’re proud of having built a working website where users can enter parameters and instantly see how much ownership they would accumulate over time for any available apartment.

What we learned

We learned how important it is to invest time into refining the core concept and validating its financial feasibility before building anything.

What's next for rent2own

For this first prototype, we focused our calculations and data on Munich. The next step is to expand the model to other cities, compare different housing markets, and adapt the parameters to local conditions.