Open Credit Scoring

Building open infrastructure for trustworthy AI credit decision systems.

Open Credit Scoring advances causal AI, open standards, and governance-by-design for credit scoring and underwriting.

Causal model positioned between antidiscrimination law and supervised machine learning

Why proprietary credit scoring slows innovation

Credit scoring has become critical financial infrastructure, but much of today's infrastructure remains proprietary, opaque, and difficult to independently evaluate. Closed scoring systems can limit scientific reproducibility, slow ecosystem-wide innovation, and make it harder to build AI systems that are transparent, governable, and trusted.

Closed systems limit reproducibility
Incumbents optimize for stability, not paradigm shifts
Trustworthy AI requires open technical infrastructure

Credit scoring needs a new foundation.

Credit scores shape access to mortgages, auto loans, credit cards, housing, and economic opportunity. Yet the technical infrastructure behind these decisions remains difficult to inspect, contest, and govern. As AI enters underwriting, the challenge is no longer just better prediction. The challenge is building decision systems that are transparent, causal, auditable, and safe by design.

Beyond black-box prediction

Most credit scoring systems are built around statistical prediction.

But high-stakes financial decisions require more than accurate predictions. They require systems that can answer deeper questions.

Open Credit Scoring investigates how causal models can help answer these questions.

Why was a decision made?
Which data actually caused the result?
Is the model relying on a proxy for a protected attribute?
Would the decision change under a fair counterfactual?
How will the system affect consumers and markets over time?

Our approach

The goal is not simply to create another credit score.

The goal is to help establish an open technical foundation for trustworthy financial AI.

We are developing a research agenda around:

Explore the Standards Work
Causal AI for credit underwriting
Fair lending and antidiscrimination analysis
Alternative data evaluation
Explainable and governable AI systems
Systems thinking for financial AI
Open standards for high-stakes decision systems

Why now?

AI is rapidly entering credit underwriting, lending, insurance, housing, and other high-stakes financial systems.

At the same time, institutions face growing pressure to improve transparency, reduce bias, manage regulatory risk, and maintain public trust.

Financial AI should be accurate, transparent, governable, and safe by design.

Build the future of trustworthy financial AI

Open Credit Scoring is for researchers, financial institutions, standards experts, policymakers, consumer advocates, and technology builders working to modernize credit decision systems.

We are building an open ecosystem for the next generation of credit scoring and financial AI.

Researchers
Financial institutions
Standards experts
Policymakers
Consumer advocates
Technology builders