Loss runs are critical for assessing a merchant’s historical insurance claims and ongoing exposure. These documents reveal coverage timelines, frequency and severity of losses, and whether claims remain open or closed.
When submitted manually, errors like missing policy years, incorrect totals, or outdated coverage can compromise underwriting decisions.
Heron automates validation for loss runs, checking parsed and scrubbed data for accuracy, completeness, and consistency. It confirms that claim totals align with reported figures, that coverage dates match expectations, and that all required sections are present.
Validation is the final safeguard before underwriting begins, making sure every data point represents reality.
By automating validation, Heron replaces time-consuming manual reconciliation with a fast, repeatable process that eliminates human error and speeds deal movement from intake to funding.
Use Cases
- Reconcile claim totals and counts: Heron verifies that reported totals equal the sum of individual claim line items. Any mismatch creates a flag for quick human review.
- Confirm complete coverage periods: Validation logic ensures that no months or policy years are missing within the requested time frame.
- Check open claim status accuracy: Heron confirms that claims marked as “open” have valid reserve values and recent activity dates.
- Detect conflicting carrier or policy data: If a document lists different carriers or policy numbers than expected, Heron flags the inconsistency immediately.
- Verify date consistency: Effective and expiration dates are tested for chronological logic, avoiding overlaps or negative durations.
- Identify anomalies in incurred vs. paid amounts: When incurred losses are lower than paid losses or totals exceed policy limits, Heron marks the issue clearly for verification.
These checks make sure underwriters never base decisions on incomplete or contradictory data.
Operational Impact
Automated validation strengthens reliability across every stage of underwriting.
- Accuracy: Every data point is cross-checked automatically, reducing manual review errors.
- Speed: Validation runs seconds after parsing, so exceptions appear early in the queue.
- Confidence: Teams trust that “ready” documents truly meet internal completeness standards.
- Transparency: Each validation step logs a pass/fail result for full audit visibility.
- Scalability: Hundreds of loss runs can be validated concurrently without additional headcount.
Validation automation turns a once tedious quality step into a silent engine of data integrity.
Validation Logic and Controls
Heron applies a structured set of validation rules. Each rule focuses on accuracy, logic, and completeness.
- Field-level validation: Confirms that mandatory fields (carrier, policy number, effective date, and expiration date) exist and are readable.
- Cross-field validation: Checks relationships between fields, such as ensuring paid ≤ incurred ≤ limit.
- Structural validation: Confirms that tables, columns, and page layouts match expected templates.
- Temporal validation: Ensures that coverage dates align with underwriting timeframes and no future-dated claims exist.
- Value range validation: Flags totals that exceed policy thresholds or fall below credible minimums.
- Duplicate validation: Detects identical loss runs previously validated to prevent redundant processing.
Together, these steps produce a clean, trustworthy dataset before underwriting review.
Exception Management
Not every loss run passes every validation rule. Heron’s structured exception handling maintains flow without introducing delays.
- Flagged for review: Items with clear errors move to a validation queue for fast human review.
- Auto-correct minor issues: Formatting inconsistencies, such as date spacing or punctuation, are corrected automatically.
- Batch escalation: If multiple loss runs fail the same check, the issue triggers a batch alert for upstream resolution.
- Version history tracking: When corrected files arrive, Heron overwrites old versions while keeping audit lineage intact.
These guardrails make validation self-sustaining and resilient under volume pressure.
Cross-Team Collaboration
Validation keeps everyone aligned on the same truth.
- Underwriters: See only verified, ready data with clear exceptions noted.
- Brokers: Receive structured missing-info requests tied to specific validation failures.
- Ops teams: Monitor dashboard-level metrics like error types and correction turnaround times.
- Managers: Gain visibility into recurring errors and can address systemic issues with brokers or carriers.
Collaboration improves when validation creates shared trust in the data.
Quality Assurance Metrics
Validation automation delivers measurable improvements across multiple performance indicators.
- Error detection rate: Over 90% of formatting and data inconsistencies are caught before underwriting sees the file.
- Exception closure time: Average correction cycle drops from days to hours.
- Field accuracy: Verified data accuracy consistently exceeds 98%.
- Manual rework reduction: Fewer than 5% of records require secondary review after rollout.
- Underwriting readiness time: Submissions become ready to underwrite up to 70% faster.
Metrics prove that validation is not just a safeguard; it’s a measurable performance driver.
Risk and Compliance Alignment
Validation directly supports compliance and audit readiness.
- Audit trail completeness: Each validation event logs the date, rule, and result.
- Data provenance: Links every validated field back to the original document source.
- Regulatory traceability: Facilitates documentation required for financial or insurance audits.
- Access control: Validation steps respect permission hierarchies to protect sensitive claim data.
- SOC 2 Type II standards: All processing and logging occur within certified infrastructure.
These measures guarantee that Heron’s validation process meets both operational and regulatory expectations.
Implementation Best Practices
Teams can get reliable validation results by focusing on setup clarity and continuous tuning.
- Define critical fields: Align with underwriting teams on which data points are mandatory for funding readiness.
- Set thresholds for exceptions: Determine when to route a case to human review based on confidence scores.
- Integrate early in the workflow: Run validation right after parsing to catch issues before documents enter underwriting.
- Review validation logs weekly: Monitor failed checks and recurring anomalies to refine rules.
- Maintain alignment with appetite rules: Tie validation criteria to current underwriting guidelines for consistency.
A controlled implementation makes validation robust, accurate, and trusted from day one.
Business Outcomes
Validation creates a stronger foundation for scaling operations without increasing overhead.
- Reduced funding delays: Issues get caught before they slow down deal progression.
- Better decision quality: Underwriters act on clean, verified data only.
- Lower downstream error costs: Prevents mispriced deals and reissued decisions.
- Improved broker relationships: Brokers receive precise feedback instead of vague rejections.
- Greater operational visibility: Managers track validation performance and use data to improve processes.
The combined effect is faster funding, fewer disputes, and higher portfolio quality.
Benefits of Using Heron for Validating Loss Runs
- Speed: Automated checks run instantly, accelerating underwriting readiness.
- Accuracy: Field and cross-field checks eliminate inconsistent or incomplete data.
- Scalability: Processes high volumes without sacrificing precision.
- Transparency: Clear audit trails and logs support accountability.
- Reliability: Consistent, repeatable logic prevents subjective decision-making.
Heron’s validation workflow transforms data hygiene from a burden into a competitive advantage.
FAQs About Validate for Loss Runs
How is validation different from scrubbing?
Scrubbing identifies missing or inconsistent data, while validation confirms that all parsed and scrubbed fields are accurate and logically correct. Validation is the final checkpoint before write-back or underwriting.
What happens when a validation check fails?
The system routes the document to a review queue with a specific failure reason. Minor errors like date formatting can auto-correct, while structural or data issues require quick human confirmation.
Can Heron learn from recurring validation errors?
Yes. Heron tracks failure patterns and refines validation logic over time. Frequent false positives lead to updated thresholds or rule adjustments for greater efficiency.
How does validation improve reporting accuracy?
Clean, validated data ensures consistent metrics across carriers, periods, and programs. This consistency improves internal dashboards, appetite analysis, and portfolio tracking.
How secure is the validation process?
Heron runs validation under SOC 2 Type II compliance with encrypted data handling, strict access controls, and full change logs. Every validation step is auditable and traceable back to the original source file.
