Articles
Application fraud checks for deciding which applications to refer
Learn how to test application mismatches against your own book and decide which checks should send an application to human review.
Application fraud after refusal and which cases need review
Decide which approvals after refusal deserve a client-level flag and which store patterns warrant review. The evidence separates useful client flags from store rankings that reflect product mix.
Changed documents in credit cases and what should rerun
Use the changed input to see which tasks must run again and which reviews must reopen. Then set freshness on the decision that needs current data.
Credit score bias checks before you release a changed score
Learn how to test whether near-equal approval rates hide group differences inside score bands, then decide which field to investigate before release.
Reject inference: test each decline rule before replacing it
See what approved-only scorecards and reject inference methods can tell you, then use a random test arm to decide whether each decline rule should stay.
What ArkOwl can reveal about an email address
ArkOwl shows the history behind an email address, including how long it has been seen and where it has accounts. That evidence helps fraud teams distinguish an established address from one that may be difficult to trust.
How many bads does a credit model need?
Three hundred bads is not a pass mark for a scorecard. The answer depends on the model's expected Gini, the parameters the build will try, and how precisely you need to know the bad rate behind pricing and provisioning.
How to use Trestle IQ Decision Signals for better anti-fraud
A fraud or credit team evaluating an identity data service needs to know what its checks cover and where the call belongs in a decision flow. Trestle IQ Decision Signals combines name, phone, address, email and IP checks with a composite identity score, with component results to read beside the policy action.
Why product attributes make your scorecard look strong and should not be in it
A public SBA loan analysis found that product attributes can dominate a scorecard because the lender chose them, while borrower attributes carry less separation. Test the top five characteristics by asking who sets each one, then move lender-set choices into a visible cutoff.
How life insurance underwriting turns an application into terms
Life underwriting does not reduce every application to accept or reject. It starts with standard mortality, adds or removes the effects of relevant factors, and then maps the result to terms such as standard rates, a loading, an exclusion, postponement, or decline.