Extract Data from Loan Applications Automatically
Upload any loan application form and get applicant details, loan amount, income, employment, and collateral information extracted as structured data in seconds.
Used by banks, lending institutions, mortgage brokers, and loan origination platforms worldwide.
Stop manually entering loan application data into your origination system
Keying applicant details, income figures, and loan parameters from paper or PDF applications into your LOS is slow, creates data entry errors, and delays credit decisions.
❌ Before ParserBee
- Open each loan application form and read all fields manually
- Re-enter applicant name, income, employer, and loan details into your LOS
- Risk errors on income and loan amount figures that affect credit decisions
- Process application intake in batches delaying approvals
- Struggle to compare applications consistently without structured data
✅ After ParserBee
- Upload applications via browser or API as they arrive
- Extract all fields including income, employment, and collateral automatically
- Push structured data into your LOS for immediate credit assessment
- Validate required fields are complete before entering the credit queue
- Process applications in real time — no manual intake backlog
How ParserBee Parses Loan Applications
Three steps from document to structured data — no templates or training required.
Upload the Document
Upload a PDF, PNG, JPG, or WebP file. Multi-page documents are processed as a single job.
AI Extracts All Fields
ParserBee identifies and extracts every field automatically — no training or configuration required.
Get Structured Data
Download as JSON or CSV, or use the API to push data directly into your systems on upload.
Fields Extracted from Loan Applications
The template comes pre-built with these fields. Add, remove, or rename any field before saving.
Sample Extracted Output
Upload a loan application and ParserBee returns a structured table like this — automatically.
| Field | Extracted Value |
|---|---|
| Applicant Name | Brandon Osei-Mensah |
| Date of Birth | 14 Aug 1988 |
| Address | 72 Harbour Rd, Auckland NZ 1010 |
| Loan Type | Home Loan |
| Loan Amount | $620,000.00 |
| Loan Term | 30 years |
| Loan Purpose | Purchase of primary residence |
| Employment | Employed — Permanent |
| Employer | Meridian Engineering Ltd |
| Monthly Income | $9,200.00 |
| Credit Score | 742 |
Every field is pulled directly from the document. You define what to extract — ParserBee does the reading.
Who Uses This Template
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Frequently Asked Questions
What data is extracted from a loan application?
Applicant name, DOB, address, phone, email, loan type, loan amount, purpose, term, employment status, employer name, monthly income, existing liabilities, collateral offered, and credit score.
Does it work with home loan, personal loan, and business loan applications?
Yes. ParserBee adapts to any loan application format regardless of loan type or lender.
Can it handle scanned paper application forms?
Yes. Scanned forms are processed by OCR and return the same structured output as digital PDFs.
How do I push extracted data into my loan origination system?
Use the REST API to map extracted fields to your LOS application object directly or via an integration platform.
What if the applicant leaves fields blank?
Blank fields are returned as null. Your LOS can flag incomplete applications for follow-up before entering the credit queue.
Related Templates
Start extracting loan application data automatically today
Free to try. No credit card required. Works on your first upload.
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