VeraScore™ is calculated using a deterministic, rules-based algorithm that measures consistent patterns in income, spending and savings to give you an objective, transparent picture of a borrower’s financial health.
For financial institutions
Understand members’ real financial capacity using live financial behavior, not just a bureau file.
Automate analysis and lower manual review overhead across your lending operation.
Align with your community mission, with an audit trail for every score.
For your members
Financial health reflects lived experience, not past credit missteps.
Transparent insights that help them manage and improve their score.
Access to products that match their real capacity and goals.
Recognizes cash flow, savings habits and stability, often the strengths of people who rarely borrow.
How it works
VeraScore uses bank-grade encryption to securely read verified data like deposits, bills and savings. VeraScore does not move money, sell data, or access passwords.
The score is computed from the connected data, scored 0 to 100 across six factors, with every number traceable.
Once shared, the member’s VeraScore and factors appear in your Lender Dashboard. Your staff can view the member’s VeraScore along with personalized recommendations for banking products.
Nothing reaches the institution that the member has not authorized. That is what makes a score available for applicants a bureau file describes thinly or not at all.
What the score measures
A credit file sees debt and payment history. It never sees income, spending or savings. Each of these is a financial measurement, scored from 0 to 100 and traceable to the data behind it.
Whether money arriving covers money going out, measured monthly for steadiness. A direct read on whether a borrower can carry a new payment.
Whether obligations were met on time over the last two years. The one measure a bureau file already gives you, now alongside five more.
How much of gross monthly income is already committed to debt service, measured against deposits you can verify rather than income the applicant states.
How high-interest borrowing is handled, from credit cards to payday loans. Separates a borrower using revolving credit as a tool from one relying on it.
How many months of expenses liquid accounts could cover with no income at all. A direct read on resilience to a job loss or a shock.
Whether reserves are growing month over month relative to income. Direction of travel, not just a point-in-time balance.
Every factor traces back to the account data behind it, with an audit trail for any scored month.
Model governance
VeraScore is produced by fixed formulas, fixed weights and versioned code. The same inputs and the same version return the same score, which is what makes the output defensible in front of a credit committee or an examiner.
Fixed formulas, fixed weights, versioned code.
The same inputs and version return the same score.
Every factor traces back to the numbers behind it.
Summary, breakdown, calculation and sources for every scored period.
The number is produced by deterministic rules. Applied AI sits outside the scoring path, where it turns results into personalized recommendations. It never produces the score.
Applied AI
Delivers personalized recommendations to help members improve their VeraScore over time.
Matches members with the right financial products or services based on verified financial health.
Two different pictures
We are not replacing the credit file. We are adding the view it was never built to give you.
| Benefit | VeraScore™ | Credit score |
|---|---|---|
| Transparency in how scores are calculated | Yes | No |
| Consideration of cash flow and assets held | Yes | No |
| Can measure ability to pay with limited credit history | Yes | No |
| Data control stays with the consumer | Yes | No |
Comparison describes category characteristics, not a benchmark against any named scoring product.
Fit
Where manual underwriting effort is highest and mission alignment is explicit.
VeraScore looks at the whole financial life of every applicant, not a narrow segment. That includes gig and 1099 earners, the self-employed and newcomers, whose strengths a bureau file often misses entirely.
Chief lending officers who want qualified volume, risk officers who want evidence, and chief executives who want to serve their communities.
We will walk your team through a sample borrower profile and show you exactly what you are not seeing today.