Anomaly Detection
Advanced identification of hidden inconsistencies and potential
fraud risk signals in borrower entity documents.
EntityScanAI analyzes borrower entity documents at a deeper structural level to detect risks often missed by manual review alone.
See which document inconsistencies warrant closer review, so your team can focus its attention.
EntityScan AI does not determine the presence of fraud. It identifies document-level anomalies and risk signals to support further review.
What EntityScan Looks For
EntityScan AI surfaces the following categories of document-level anomalies that may warrant closer human review:
Visual & Structural Anomalies
Pixel-level artifacts such as ghosting, font mismatches, digital overlays, or irregular formatting that may indicate document alteration.
Document Inconsistencies
Mismatched entity details, conflicting dates or figures, or inconsistencies across borrower-submitted entity documents.
File-Level & Metadata Signals
Unusual file creation attributes, editing patterns, or metadata indicators that may suggest alteration or redaction.
Have questions about a finding noted in your report? Ask the EntityScan Assistant to help you understand what the report says and consider next steps.