Your Next Qualified Borrower Is Already in Your Database
Banks and credit unions are sitting on a problem most don't know they have. Credit report errors are quietly blocking qualified borrowers from getting approved and costing lenders real revenue.
1 in 5 Americans carries a material error on their credit file. Those errors suppress scores, trigger denials, and push creditworthy people out of your funnel before they ever get a fair look.
Revelar changes that. As a purpose-built solution for alternative data for banks and credit unions, TrackStar AI’s machine learning engine scans your existing applicant data, identifies suppressed credit potential, and surfaces the borrowers you should have been approving all along.
Why Alternative Data for Banks and Credit Unions Starts With Revelar
- Expand approvals without adding risk – Revelar identifies qualified borrowers who were previously declined due to inaccurate data, not actual credit risk.
- Speed up underwriting decisions – Revelar scans millions of credit files in minutes, not months. Best Egg processed 20 million historical records in under three minutes.
- Reduce disputes and FCRA friction – when you catch errors early, you reduce the downstream compliance burden that comes with incorrect denials.
- Deploy inside your existing environment – Revelar runs in a secure Docker container inside your VPC. Zero data leaves your infrastructure.
- No rip-and-replace required – Revelar plugs into your existing credit decisioning stack without rebuilding your risk models from scratch.
Alternative Data for Banks and Credit Unions in Practice
Best Egg, a leading consumer lending platform, used Revelar to scan 20 million historical credit reports. They found 3.4 million consumers carrying credit report errors, a nine-figure net-new lending opportunity they didn’t know existed.
Within six months of deploying Revelar, Best Egg saw a 40% increase in cross-sell opportunities and a 10% reactivation of dormant applicants. They did it without acquiring a single new customer.
For banks and credit unions, this is exactly the kind of opportunity hiding in your existing data. Your applicant database already contains borrowers who deserve a second look. Revelar shows you who they are.
Built for the Way Banks Actually Work
Revelar is trained on more than 30 million dispute outcomes across all three major credit bureaus, Equifax, Experian, and TransUnion. That is nearly two decades of proprietary remediation intelligence built into a single machine learning engine.
It does not use LLMs or external API calls. It does not move your data. It meets bank-grade compliance standards and integrates in weeks, not quarters.
If your underwriting team is making decisions based on flawed data, you are not just losing approvals. You are losing the revenue that comes with them.
Core Solutions
Ready to See What's Hidden in Your Data?
Book a discovery call and see how Revelar uncovers the lending opportunities already inside your existing credit files.
