The rental market often excludes millions of people—such as young adults, immigrants, or gig workers—because traditional credit scores don’t capture their financial reliability. This creates unnecessary barriers to housing, pushing many toward unstable or exploitative living situations. One way to address this could be by creating an alternative credit-scoring system designed specifically for rentals, using non-traditional data to assess an applicant’s trustworthiness.

How It Could Work

Instead of relying solely on credit history, this system could analyze data like:

• Rent and utility payment history
• Bank transaction patterns (e.g., consistent income deposits)
• References from previous landlords or roommates

A digital platform could aggregate this information, generate a rental-specific score, and provide landlords with clear insights. Renters might build and share profiles showcasing their reliability, similar to a professional resume but for housing. AI could update scores in real-time as new data becomes available, offering a more dynamic assessment than traditional credit bureaus.

Potential Benefits and Stakeholders

This approach could help:

• Renters who are "credit invisible" gain fair access to housing.
• Landlords reduce vacancies and screening costs with better applicant insights.
• Data partners (e.g., banks, utility companies) monetize underused information.

For adoption to take off, the system would need to demonstrate that alternative data reliably predicts on-time rent payments—something a pilot program could test.

Execution and Challenges

One way to start could be with a small-scale MVP:

1. Partner with a few landlords to manually evaluate applicants using alternative data (e.g., bank statements).
2. Develop a basic web app for renters to upload documents and landlords to review profiles.
3. Later, integrate APIs (like Plaid for bank data) to automate scoring.

Key challenges include ensuring data privacy (e.g., via zero-knowledge proofs) and regulatory compliance. However, if successful, the system could eventually expand to include more data sources, such as gig economy earnings or short-term rental reviews.

Unlike existing solutions that report rent payments to credit bureaus, this approach would bypass traditional credit systems entirely, offering faster, more inclusive assessments tailored to the rental market.