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Loan Application Bundler Audit

AI
audits a stack of loan docs against lender checklist. Detects loan type, lists missing items, surfaces eligibility issues.
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What you'll get: an audit of your loan-application bundle against a typical lender checklist (ID proofs, salary slips, bank statements, ITRs, property docs) + missing-item flags + income snapshot + eligibility-affecting issues. Not pre-approval. For another use, try AI · Table Extract.

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Private & secure
AI tools process your PDF in memory, send only the extracted text to the model, and discard everything immediately. No file is persisted on our servers.
No watermarks
Clean output, no branding, no daily limits.
Pay only for what you use
Purchased credits never expire. Cancel anytime.

Why people use Loan Application Bundler Audit

Indian loan applications (home loan, personal loan, business loan, education loan) require a stack of documents: KYC, income proof, bank statements, ITR, property docs (for secured loans). The audit detects what loan type the bundle is for, audits against the lender’s typical checklist, surfaces missing items, and flags eligibility issues before submission.

Home loan application pre-check
Before submitting to HDFC / ICICI / SBI / Bajaj Housing Finance, run the bundle through the audit. Surfaces missing items (latest 3-month payslips often forgotten, or bank statements not stamped) that would otherwise cause rejection or 3-week delays.
Business / MSME loan readiness
MSME loan documentation is dense (CMA data, projected financials, audited statements). The audit verifies the bundle has the items the lender will ask for — faster than discovering gaps mid-application.
Personal loan eligibility check
Personal loans rejected for FOIR / EMI-to-income mismatches are common. The audit calculates EMI capacity from bank statements and flags eligibility before you apply (and take a credit-bureau hit).
Education loan abroad
Foreign education loans (Avanse, HDFC Credila, banks) have detailed admission + co-borrower documentation. The audit verifies all required items present (admission letter, fee schedule, parent ITR / bank statements, university accreditation).
Loan against property / mortgage
LAP and mortgage applications need property documentation (title deeds, encumbrance certificate, property tax receipts). The audit surfaces missing property-side docs that lenders often ask for late in the process.

How Loan Application Bundler Audit works

Three steps. Sign in to run, zero retention — files never persisted on our servers.

  1. STEP 1
    Concatenate + drop your document bundle
    Combine your loan documents into one PDF (use our Merge PDF tool first), then drop. Works on home loan / personal loan / business loan / education loan / loan-against-property bundles up to 100 MB.
  2. STEP 2
    We detect + audit
    First pass detects loan type from the bundle contents (KYC + property docs → home loan / LAP; KYC + payslips + bank statements → personal loan; CMA data → MSME). Then audits against the lender’s typical checklist for that loan type.
  3. STEP 3
    Get an audit report
    Markdown output with: detected loan type / present items / missing items / eligibility flags (FOIR / DTI / property valuation gaps). Page citations link each finding back to the bundle for your review.

What makes pdfcraft ai different

  • Citations on every claim
    Every AI summary, answer, and translation links back to the page it came from. You can verify the source before relying on the output. Hallucination is bounded, not blind.
  • Pay only for what you use
    No subscription. Purchased credits never expire. Cancel anytime. Cost shown before you run — exact credit amount appears after upload.
  • Multi-provider routing, no vendor lock-in
    We balance multiple AI providers per call to optimise cost and quality. If one has an outage, the next call automatically tries another. You're not bound to a single vendor's pricing or downtime.
  • Zero retention by design
    Your PDF lives in memory only as long as the AI call needs it, then it's discarded — nothing is persisted to our servers. We don't fine-tune models on your data. Verifiable in your dashboard's audit log.
  • Honest about model limits
    When a doc exceeds the model's context window we surface that the output was truncated (we render result.wasTruncated in every AI tool's UI). When a number can't be verified from the source we flag it. No silent failures.

Frequently asked questions

Is the audit lender-specific?
Generic-checklist by default — matches what most Indian lenders ask. Specific lender variants (HDFC vs SBI vs Bajaj vs PSU banks) have minor checklist differences. The output is a strong baseline; cross-check against the specific lender’s documents-required PDF for the final submission.
Does it calculate eligibility?
Surfaces eligibility flags from the documents present (FOIR estimated from payslips + bank statements, DTI estimated, property LTV from valuation if present). These are heuristic estimates — the lender’s underwriting is more sophisticated. Use the audit estimates to know if you’re in the ballpark before applying.
What about scanned bundles?
OCR runs on scanned pages first. Most lender-submitted bundles include both clean PDFs (from KYC tools) and scanned items (property documents, older bank statements) — both work. Quality on faded / handwritten property documents is lower; flag for human review when accuracy matters.
Will it catch document age requirements?
Surfaces freshness flags (e.g. “bank statements are 4 months old; lender typically requires latest 3 months”). Useful for catching staleness before submission — common cause of rejections or processing delays.
What’s the credit cost?
3 credits per audit. Cost is fixed regardless of bundle size.
Privacy?
Bundle sent to inference provider for audit, not stored. For maximum confidentiality on financial documents (PAN, Aadhaar, bank account numbers), redact PII via Redact PDF before running the audit — the structural audit works on the redacted bundle.

Need to merge documents first?

Merge PDF combines multiple PDFs into one bundle — the prerequisite for the loan audit. Works in your browser, no signup needed for the merge step.

Try Merge PDF

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