What Is Bank Statement Parsing?
Bank statement parsing is the automated extraction and structuring of key financial information from a merchant’s bank statements. In MCA and small business lending, it is essential to understand a merchant’s cash flow, repayment capacity, and risk profile.
Typical fields derived include average daily balance (ADB), overdraft frequency, non-sufficient funds (NSFs), deposit patterns, and payments to other lenders. Operators use this process to build an accurate, consistent picture of financial health quickly.
How Does Bank Statement Parsing Work?
Bank statement parsing takes raw PDF or scanned statements and converts them into structured fields.
- Document ingestion: Bank statements arrive as email attachments, portal uploads, or API submissions.
- Recognition: The system identifies the statement format and extracts transaction-level data.
- Field creation: Key figures such as ADB, overdraft counts, and cash inflows/outflows are calculated.
- Output: Parsed fields are made available for underwriting and eligibility checks.
In Heron, bank statement parsing is a core scrubbing step.
- Parsing engine: Heron converts statements into structured fields like ADB, overdrafts, and external debt indicators.
- Risk checks: Red flags such as NSFs, negative days, and external lender payments are automatically surfaced.
- CRM write-back: Clean data is pushed directly into CRM records for immediate use.
- Next action: Underwriters receive underwriting-ready packets without needing to rekey or manually review pages.
This creates a direct path from submission to underwriting in minutes.
Why Is Bank Statement Parsing Important?
For brokers and funders, bank statement parsing is important because statements are the backbone of MCA and small business underwriting. Without automation, teams spend hours manually reviewing PDFs and spreadsheets.
Heron improves this process by reducing turnaround time, lowering error rates, and providing real-time insights. This helps funders assess deals faster and at scale.
Common Use Cases
Bank statement parsing is widely used across MCA and lending workflows.
- Calculating average daily balance to measure liquidity.
- Detecting external debt obligations through recurring ACH debits.
- Surfacing NSF events and overdraft frequency as risk signals.
- Identifying irregular deposits or payroll consistency.
- Feeding structured financial fields directly into CRM systems.
FAQs About Bank Statement Parsing
How does Heron handle bank statement parsing?
Heron parses PDFs and scanned bank statements, normalizes the data, and writes structured fields such as ADB, overdrafts, and external debt indicators into the CRM.
Why is bank statement parsing valuable for MCA brokers and funders?
It saves hours of manual review, improves accuracy, and provides underwriting-ready data within minutes, helping teams handle more volume.
What outputs should teams expect from bank statement parsing?
Teams can expect structured CRM records with key financial metrics, red flags, and decision-ready insights that replace manual spreadsheet preparation.