Not every Request for Evidence is about missing documents. A meaningful share come from inconsistencies the reviewer can see on the forms themselves — the same client described two different ways across a package. Those are the cheapest RFEs to prevent, because they're clerical, not substantive.
Most preventable RFEs come from data-entry inconsistencies: a transposed A-number, a date of birth in the wrong format, a name spelled differently across forms, or an outdated address. Filling every form in a case from one canonical client profile — instead of retyping each form by hand — keeps these facts identical everywhere, so a single review catches them.
Which data-entry errors trigger RFEs most often?
- A-number transpositions — one digit off on a single form flags a mismatch across the file.
- Date formatting — MM/DD/YYYY vs DD/MM/YYYY slips, especially for foreign-born clients.
- Name variants — middle names, maiden names, and transliterations that differ from supporting evidence.
- Stale addresses — an old address auto-remembered on one form but updated on another.
Each of these is a consistency problem. When forms are typed independently, consistency is left to human attention on every page; when they're filled from one source, it's structural.
Why does retyping make errors more likely?
Every manual re-entry of the same fact is another chance to introduce a discrepancy. Across 20–30 forms per case, the probability that at least one A-number or date drifts is high — not because anyone is careless, but because volume plus repetition is exactly the condition under which small errors appear. Removing the repetition removes the mechanism.
How does filling from one profile prevent these?
When a client's A-number, name, and dates live in a single profile and every form pulls from it, the value is either correct on all forms or wrong on all forms — and you verify it once. Tools like Filly also color-code each filled field by confidence, so low-certainty entries surface for review instead of hiding in a wall of text. The reusable-profile workflow is walked through in how to auto-fill USCIS immigration forms.
What should a pre-filing QA check include?
A short, consistent checklist beats ad-hoc review: confirm the A-number matches across every form, dates use USCIS's expected format, the name matches supporting documents exactly, and the current address is identical everywhere. When forms are filled from one profile, this check takes minutes rather than a page-by-page comparison.
Frequently asked questions
Can better data entry really lower my RFE rate?
It can reduce the clerical, consistency-based RFEs — the ones caused by mismatched numbers, dates, names, or addresses. It won't affect RFEs about the substance of a case, which are a legal matter.
Is Filly a substitute for attorney review?
No. Filly is a form-filling tool, not legal advice. It reduces re-entry errors, but you remain responsible for reviewing and filing every form.
Does it work across an entire case package?
Yes. Once a client profile exists, every form in the case fills from it, which is what keeps facts consistent across the whole package.
How is the client data protected?
Filly encrypts stored data, publishes its sub-processors, doesn't train AI on your documents, and supports deletion on request — details on the security page.