Streamline Subprime Lending Decisions

Say goodbye to guesswork and hello to enriched decisioning. Leverage reliable, data-driven, credit scores to filter prime borrowers from subprime applicants.

Get Dynamic Credit Scores With Our Data Trifecta

Powered by our patented machine learning and artificial intelligence technology, the Trust Science credit scoring algorithms combine traditional and alternative data with consent-based mobile and social data to deliver in-depth and dynamic credit scoring machine learning models and scores. Trust Science:

  • Expands scorable universe and identifies new targets who may not have a complete profile based on traditional methods (e.g. thin-file, no-file, credit Invisibles)
  • Better matches products and services to targets based on robust credit scoring machine learning models

Trust Science® uses patented algorithms to analyze publicly available digital information. We collect loan data from social media, news sources, court data, web search, transactions and more. Using sophisticated machine learning models and algorithms, we process this data to then determine the creditworthiness of individuals, business and organizations.

About Trust Science...

Impactful Results to Your Underwriting

Increase Loan Originations

Identify more creditworthy thin and no-file credit customers.

Decrease Risk Of
Defaults

Better insights into thin and no-file borrowers minimizes risk of defaults.

Improve Lending Profitability

Decrease operating expenses via Straight-Through Processing.

The Library is Open: Get More Free Resources

Infographic: Ultimate Underwriting Showdown

What happens when Trust Science goes toe-to-toe with traditional scoring methods?

Checklist: 5 Steps to Start Automated Underwriting

Ready to get started? Track your path to progress with our helpful checklist.

Testimonials

Bryan Smith

VP Sales & Marketing,
Inovatec

“Simple and powerful results for a more complete risk assessment of the individual.”

Mark Eleoff

CEO, Eden Park Inc.

“Trust Science has proven themselves to be innovative, value-added, and very customer-centric in working with us to improve our credit decisions.”