Assess credit risk
Evaluate a consumer’s ability to pay and likelihood of default leveraging our alternative FCRA-compliant score




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Traditional credit scores remain a standardized tool for assessing creditworthiness, but they increasingly fall short in today’s fast-evolving financial landscape. With rising demand for a more expansive, real-time view into consumer financial health, lenders are turning to alternative data sources like bank account activity, inquiry behavior, and tradeline performance to better assess a consumer’s ability to pay and predict potential defaults.
vCredit® is a low-friction, predictive credit risk score that leverages proprietary bank account and payment intelligence from ValidiFI’s data network.
By analyzing both historical financial behavior and current account activity, vCredit® enables lenders to:
- Offer optimized credit lines based on actual financial capacity.
- Match consumers with the right products, improving conversion and satisfaction.
- Expand approval rates by identifying creditworthy individuals.
- Optimize performance while minimizing risk through more accurate predictions of payment performance and default likelihood.
Flexible, predictive scoring
vCredit® uses a rich set of alternative financial data sourced from ValidiFI’s data network.
- Works with your application flow using PII-based input or full application data
- Multi-Signal Intelligence for stronger predictive power
- Useful for pre-qualification, lead scoring, or onboarding workflows
The value for your business
Holistic View of Consumers
Identify potential risks and opportunities not captured in traditional credit reports
Improved Decision-Making
Analyze inquiry, payment history, credit activity, and tradeline performance
Drive Portfolio Growth
Optimize decisions while minimizing risk with an FCRA-compliant score
vCredit® uncovers hidden risk signals
vCredit® helps financial institutions make smarter, faster, more precise credit decisions:
- 60% higher risk when a consumer has 6+ bank accounts associated with them over the past 180 days
- 58% higher risk with 4+ email addresses associated in the past 180 days
- Consumers with a recent NSF (R01) return are 36% more likely to repeat the same issue on their next transaction
Related resources
Related products
vFraud®
Pair with vCredit to identify suspicious activity and high-frequency changes in accounts and consumer information.
vAccount™ Suite
Validate accounts and authenticate ownership to ensure secure transactions and build trust.
vInsightsync™
ash flow insights report for a more holistic view of consumer financial behavior.
Frequently asked questions
vCredit® is a predictive credit risk score that is also FCRA compliant. Lenders and Financial service providers use vCredit® to help approve, decline, and make more accurate pricing decisions, with Adverse Action reason codes provided.
vCredit® is used by many of our lending clients to assess second look, non-prime or underbanked consumers to make better credit decisions, credit line increases, and expand their portfolios.
vCredit® is designed to be flexible and fit seamlessly into your application flow. It can generate a score using just a Social Security Number (SSN) for early-stage risk assessment, or leverage Bank Account and Routing Number (BARN) data for deeper financial insights. This flexibility allows lenders to choose the input method that best aligns with their onboarding, underwriting, or lead scoring workflows.
vCredit® delivers a highly predictive credit risk score powered by hundreds of attributes on tradelines, payment performance, and velocity metrics.
vCredit® helps predict an individual’s likelihood to default, much like traditional credit scores, but vCredit® leverages predictive bank account and payment information to provide a more accurate assessment of creditworthiness.
Yes, all customers are required to report their performance data as we are a give-to-get data model. By doing this, all customers gain tremendous value from accessing a much larger database of information than they would without data contribution across the network.