What Is an Accuracy Rate?
An accuracy rate refers to the percentage of fields or submissions that are processed correctly by automation.
In MCA and small business lending, this often means checking whether parsed values like average daily balance, NSF counts, or dates match what a human reviewer would have keyed manually.
This metric is most relevant in intake and scrubbing workflows. Operators rely on it to evaluate automation effectiveness and to understand how often exceptions must be raised due to incorrect parsing or mismatches.
How Does an Accuracy Rate Work?
An accuracy rate is calculated by comparing correct outputs to total outputs.
- Parsing step: Fields such as balances, deposit amounts, or ID numbers are extracted from documents.
- Validation: Results are compared against source documents or ground truth.
- Rate calculation: The percentage of correct outputs versus total outputs is calculated.
- Exception handling: Errors or uncertainties are routed into manual review, which prevents them from blocking the overall flow.
In Heron, the accuracy rate is a central performance metric for scrubbing.
- Automated checks: Bank statements, IDs, and decision emails are parsed into structured fields.
- Confidence scoring: Each output is assigned a confidence measure, helping route uncertain cases to reviewers.
- Exception queues: Incorrect or unclear results trigger human-in-the-loop review without holding up clean cases.
- Next action: Teams receive underwriting-ready records with validated fields, while edge cases are flagged separately.
This keeps accuracy high while maintaining throughput.
Why Is the Accuracy Rate Important?
For brokers and funders, accuracy rate is important because incorrect fields cause rework, decision delays, and potential funding mistakes. A high accuracy rate builds confidence in automation and reduces the share of items requiring manual review.
Heron directly impacts this metric by combining scrubbing logic, completeness checks, and exception handling. Even when accuracy is not perfect, Heron keeps work flowing by isolating exceptions without slowing down the majority of submissions.
Common Use Cases
Accuracy rate is applied in performance measurement and quality assurance.
- Tracking how often bank statement parsing produces correct balances.
- Measuring the correctness of decision email parsing into CRM fields.
- Monitoring error rates when mapping parsed data to CRM picklists.
- Comparing accuracy before and after automation improvements.
- Using the accuracy rate as a KPI in SLA or vendor reporting.
FAQs About Accuracy Rate
How does Heron maintain an accuracy rate at scale?
Heron combines automated scrubbing with confidence scoring and exception routing. This ensures that only clean, high-confidence data is written back to the CRM.
Why is the accuracy rate valuable for MCA brokers and funders?
It shows whether automation can be trusted to deliver underwriting-ready data. High accuracy means less manual work, fewer rechecks, and faster decision cycles.
What outputs should teams expect from tracking accuracy rate?
Teams receive clear percentages showing automation correctness. Reports also reveal trends over time, helping to monitor progress and refine workflows.