Bank statements carry the most reliable picture of a merchant’s actual cash behavior. They reveal deposits, withdrawals, fees, and daily balances that drive underwriting and pricing.
Before underwriters can trust those numbers, the statements need to be scrubbed for completeness, accuracy, and risk signals.
Manual scrubbing is slow and inconsistent. Teams flip through pages, look for gaps, and try to spot issues while juggling multiple formats. That creates delays and produces uneven results across analysts and shifts.
Heron automates scrubbing the moment statements enter the system. The product checks page continuity, validates periods, and extracts core metrics while flagging risk patterns like NSFs, overdrafts, and stacked obligations. It converts messy PDFs into decision-ready facts.
Scrub results write back into the CRM as clean fields and flags. Deals move forward with clear status, fewer reworks, and less back-and-forth with brokers. Underwriters gain confidence because they see structured numbers tied to the original pages.
Use Cases
Scrubbing touches every packet that contains bank statements. These focused scenarios show how Heron accelerates work and reduces errors.
- Verify completeness quickly: Heron checks page counts and date sequences, then marks gaps for the follow-up.
- Detect duplicates clearly: The system identifies re-sent statements and suppresses repeats to keep queues clean.
- Surface NSF and overdraft patterns: Scrub flags counts and dates so appetite checks can run early.
- Calculate average daily balance: Heron derives ADB consistently across banks and templates.
- Spot external ACH debits: The system maps recurring debits to reveal existing advances and loans.
- Identify negative balance days: Scrub tallies negative days as a stability signal for underwriting.
- Normalize month coverage: Heron aligns partial months and highlights missing periods for quick resolution.
- Write decisive fields back: Results land in the CRM with structured values and readable notes.
Operational Impact
Automated scrubbing compresses intake-to-decision time. Teams get reliable fields in minutes, which shortens queues and reduces touches per submission.
Exception rates fall because incomplete or risky packets surface early with clear reasons. Managers see accurate throughput and can allocate reviewers only where needed.
Operational KPIs most affected:
- Turnaround time: Shorter time from receipt to underwriting-ready status.
- Touches per submission: Fewer manual checks on complete packets.
- Exception rate: Lower, with precise reason codes for quick fixes.
- Backlog burn-down: Faster clearing of Monday and month-end spikes.
- Cost per submission: Reduced labor and fewer escalations.
Quality Controls and Validation
Heron’s scrub step includes layered checks that make sure results are trustworthy. Each control narrows the gap between documents and the fields underwriters rely on.
- Document integrity checks: Page counts, period continuity, and legibility thresholds run before downstream work.
- Cross-field math checks: Opening, transactions, and closing values reconcile within configured tolerances.
- Confidence scoring per field: Low-confidence items route to a short review lane with page references.
- Tampering signals: Suspicious edits, mismatched fonts, or duplicated lines create a fraud flag.
- Traceable sources: Every field links back to the page and coordinate locations for instant verification.
Configuration and Integration
Scrub fits into the existing intake path and writes back to the system of record without rebuilding tools. The setup matches how teams already work.
- Inbox, portal, and API intake: Statements flow into Heron from the channels teams use today.
- Field mapping to CRM: ADB, NSFs, overdrafts, and external debits map to specific fields.
- Naming and storage rules: Files keep standardized names and are attached to the right records.
- Status updates and routing: Deals move to underwriting-ready when the scrub is clean, or to review with reason codes.
- Scalable throughput: Volume surges are absorbed without quality loss.
Implementation Best Practices
A structured rollout makes scrub accuracy high from day one. These steps keep quality strong as volume grows.
- Prioritize common banks first: Start with top templates, then expand coverage by frequency.
- Set practical thresholds: Choose variance and confidence levels that match actual appetite.
- Create a daily review lane: Clear low-confidence items every day to keep queues moving.
- Share a broker checklist: Ask for full months, readable scans, and complete page sets.
- Spot-check weekly with samples: Compare fields to source pages and tune rules as needed.
- Track exception reasons: Fix top drivers at the source to lower rework.
- Document field definitions: Write clear definitions so teams interpret outputs the same way.
Benefits of Using Heron for Scrubbing Bank Statements
- Speed: Automation turns page flipping into instant results that underwriters can use.
- Accuracy: Layered checks and confidence scoring reduce errors and rework.
- Scalability: High volumes and spikes no longer require added processors.
- Consistency: Every statement is scrubbed to the same standard across teams.
- Clarity: Fields and flags link to sources so reviews are quick and decisive.
FAQs About Scrub for Bank Statements
What does scrubbing bank statements mean in practice?
Scrubbing means checking statements for completeness, validating math and periods, and extracting key metrics and flags. Heron performs these steps automatically and writes results into the CRM.
Which fields are typically produced by scrub?
Common fields include average daily balance, total monthly deposits, NSF count, overdraft count, negative days, and external ACH debits. Flags may include tampering, duplicate statements, and missing months.
How does Heron handle incomplete or out-of-order statements?
Heron checks page counts and date continuity at intake. If pages or months are missing, it flags the issue and can trigger a templated missing-info request while leaving the rest of the pipeline unblocked.
How are accuracy and confidence managed?
Each parsed and scrubbed field carries a confidence score. Low-confidence items move to a short review queue with links to the exact page locations for fast confirmation.
Can we customize scrub rules to match eligibility criteria?
Yes. Operations leaders can set thresholds and logic to match program appetite, such as minimum average daily balance or NSF limits. Those results can route deals automatically.
