Cash flow statements give brokers and funders a real look into how a business manages cash, not just profits on paper.
They outline inflows and outflows across operations, investments, and financing, revealing liquidity and repayment potential. But these documents are often formatted inconsistently, making manual parsing slow and error-prone.
Heron automates the parsing of cash flow statements, converting unstructured PDFs, scans, and attachments into clean, structured data fields.
Instead of human operators typing line items like “Net Cash from Operations” or “Cash Used in Financing,” Heron’s system extracts them instantly and maps each value to a standardized format ready for underwriting.
By automating parsing, Heron bridges the gap between intake and decision, turning static financial statements into live data for faster funding decisions.
Use Cases
- Extract structured data from varied formats: Heron identifies and parses cash flow statements from different brokers, even if templates vary.
- Detect and separate activity types: The system categorizes sections such as operating, investing, and financing cash flows for precise analysis.
- Capture key financial metrics: Heron pulls out totals like “Net Cash Flow,” “Ending Cash Balance,” and “Net Increase in Cash.”
- Normalize currency and formatting: All values are standardized for easy comparison across deals.
- Flag missing or inconsistent values: If a section or total is missing, Heron marks the record for review before CRM write-back.
- Feed parsed data into underwriting systems: Clean, validated numbers sync directly to CRM fields and analytics dashboards.
Each of these use cases eliminates manual effort, creating a continuous data flow that supports faster, more accurate underwriting.
Operational Impact
Parsing automation transforms how cash flow data is managed at scale.
- Speed: What once took hours of manual entry happens in seconds.
- Accuracy: Automated parsing removes human transcription errors and ensures numerical integrity.
- Scalability: Teams can process ten times more submissions without adding headcount.
- Visibility: Parsed data becomes searchable and filterable for instant reference.
- Reliability: Consistent formatting keeps systems synchronized across brokers and funders.
These improvements shorten the underwriting cycle while improving decision quality.
Parsing Logic and Workflow
Heron’s parsing workflow is designed to handle unstructured data from both digital and scanned documents.
- Optical character recognition (OCR): Text is extracted from scanned PDFs or images.
- Line-item detection: Heron identifies rows and columns corresponding to cash flow activities.
- Section mapping: Each detected activity is categorized as operating, investing, or financing.
- Value extraction: Numerical data, including totals and subtotals, is captured with contextual labels.
- Error detection: Inconsistent or mismatched totals are flagged for human review.
- Data output: Clean, structured results are converted into standardized fields for CRM or analytics systems.
This process guarantees that even low-quality or inconsistent files yield usable financial data.
Governance and Quality Assurance
Heron’s parsing system follows strict standards for accuracy and auditability.
- Audit trails: Every parsed document is logged with timestamps and processing metadata.
- Version control: Parsed data retains the original file reference for traceability.
- Confidence scoring: Each extracted value is assigned a confidence level that determines whether it passes automatically or requires review.
- Data integrity checks: Summations and subtotals are verified to catch discrepancies.
- SOC 2 alignment: Data parsing complies with recognized security and reliability frameworks.
- Exception queues: Low-confidence or incomplete parses are routed to reviewers for quick correction.
This governance layer keeps automation reliable and transparent in high-stakes lending environments.
Integration with Underwriting Systems
Parsed data only becomes powerful when it connects seamlessly to downstream systems. Heron’s integrations make that possible.
- CRM field mapping: Parsed cash flow metrics are automatically mapped to predefined CRM fields.
- Policy rule triggers: Parsed totals can trigger automated underwriting workflows or eligibility checks.
- Cross-document comparison: Cash flow data aligns with P&L and balance sheet figures for consistency verification.
- Real-time updates: When new statements arrive, parsed values overwrite outdated ones in connected systems.
- Data aggregation: Historical parses feed into long-term portfolio analytics.
- Automated reporting: Funders can generate deal summaries and performance dashboards instantly.
These integrations ensure that parsed data translates directly into actionable insight.
Implementation Best Practices
Teams introducing Heron’s parsing feature can follow a few practical steps for smooth deployment.
- Define key data fields: Decide which cash flow items are essential for underwriting.
- Review data mappings: Match extracted fields to CRM or LOS systems accurately.
- Run pilot parses: Start with a small set of broker submissions to validate accuracy.
- Set review thresholds: Choose confidence levels for automatic approval versus manual review.
- Monitor exception trends: Track which document types or brokers cause the most parsing errors.
- Refine continuously: Use exception feedback to train and improve Heron’s parsing accuracy over time.
This methodical rollout ensures high accuracy and fast adoption across operational teams.
Benefits of Using Heron for Parsing Cash Flow Statements
- Speed: Turns complex financial statements into structured data instantly.
- Accuracy: Captures key financial values without manual intervention.
- Scalability: Handles high document volume effortlessly.
- Compliance: Maintains audit trails for every parsed record.
- Consistency: Delivers standardized output across brokers and deals.
Heron’s parsing automation transforms static documents into dynamic, reliable financial data pipelines that power faster and smarter underwriting.
FAQs About Parse for Cash Flow Statements
How does Heron parse cash flow statements?
Heron reads the document’s text and structure to extract financial data from the operating, investing, and financing sections. It then converts those figures into structured, labeled data fields ready for CRM integration.
Can Heron handle scanned or low-quality PDFs?
Yes. Heron uses advanced OCR to interpret scanned files and reconstruct missing characters using contextual models. Even poor-quality submissions yield accurate data with minimal review.
What happens when a total doesn’t match?
If subtotals or net cash figures are inconsistent, Heron flags the document and routes it to an exception queue. The underwriter can then verify or correct the discrepancy.
How does parsed data flow into underwriting systems?
Once parsed, data is mapped directly into the CRM or decision engine, populating financial fields automatically. This gives underwriters instant access to structured, validated numbers.
How does Heron maintain parsing accuracy?
Heron uses confidence scoring, machine learning feedback, and rule-based validation to keep accuracy rates high. Continuous updates improve recognition for new document formats and layouts.
