What Are Fraud Flags?
Fraud flags are specific markers that suggest a document or dataset may have been altered, falsified, or used to hide key information.
In MCA and small business lending, common fraud signals include tampered bank statements, duplicate submissions with mismatched details, or suspicious transaction patterns.
Fraud flags typically appear during the scrubbing process, when documents are parsed and validated. Operators use them to decide whether a deal should be escalated, declined, or verified further before moving forward.
How Does Fraud Flags Work?
Fraud flags are generated by checking submissions for unusual or inconsistent patterns.
- Document review: Statements and IDs are scanned for irregular formatting, missing elements, or suspicious edits.
- Transaction analysis: Flows such as repeated identical deposits, sudden spikes in balances, or repayment to multiple funders are flagged.
- Cross-checking: Applicant details are compared across submissions to detect mismatches.
- Risk scoring: Submissions with multiple red flags are escalated for manual review.
In Heron, fraud flags are integrated into automated scrubbing.
- Automated detection: Heron scans statements for signs of tampering, such as repeated fonts, duplicate transactions, or page gaps.
- Signal surfacing: Fraud indicators like excessive overdrafts, manipulated deposits, or mismatched IDs are flagged.
- Structured output: Results are written into the CRM as risk fields alongside the packet.
- Action routing: Deals with strong fraud flags are routed to exception queues, while clean deals move directly to underwriting.
This helps teams spot potential fraud instantly without relying on manual inspection.
Why Are Fraud Flags Important?
For brokers and funders, fraud flags are critical to preventing financial losses. Funding based on manipulated statements can result in default or recovery challenges.
Automated fraud detection ensures consistency, scale, and speed. With Heron, teams make sure every submission is reviewed for red flags without slowing down deal flow.
Common Use Cases
Fraud flags appear across many underwriting scenarios.
- Detecting tampered bank statements with altered balances.
- Flagging repeated transactions that suggest artificial revenue.
- Surfacing mismatched applicant details across multiple submissions.
- Identifying duplicate packets from different ISOs.
- Routing flagged deals to manual review before funding decisions.
FAQs About Fraud Flags
How does Heron generate fraud flags?
Heron automatically reviews documents during scrubbing, checking for manipulations, inconsistencies, and risk signals. These are logged as structured outputs in the CRM.
What are common fraud indicators in MCA submissions?
Examples include missing statement pages, unusual formatting, repeated deposits, mismatched applicant details, and repayment flows to multiple lenders.
What happens when a fraud flag is raised?
The submission is routed to an exception queue for human review. Underwriters can investigate further before making a funding decision, preventing risky deals from slipping through.