Products
© Fiskil 2026. All rights reserved.
Lending
Loan Application Prefill
Loan applications require extensive personal and financial information. Fiskil automatically extracts verified data from banking transactions to pre-fill applications, dramatically reducing completion time and improving accuracy.
Manual data entry creates friction, leading to high abandonment rates and inaccurate information.
Applications take 20-45 minutes to complete manually
60-70% of applicants abandon before completion
Manual data entry introduces errors
Applicants don't have all required information available
Verification of manually entered data adds processing time
Automatically extract and pre-fill application fields using verified information from bank accounts and transactions.
Extract name, address, contact details, and date of birth from account information.
Identify employer name, employment length, and income from transaction patterns.
Automatically calculate income from salary deposits and other income sources.
Summarize expenses by category to pre-fill living expense fields.
Add one-click application prefill to your lending platform.
Applicant clicks "Connect Bank Account" and authorizes access through CDR consent.
API analyzes transactions and account details to extract required application fields.
Application form is automatically populated with verified information from banking data.
Applicant reviews pre-filled data, makes any corrections, and submits in minutes.
Machine learning extracts relevant information from unstructured transaction data.
Automatically map extracted data to your specific application form fields.
Each pre-filled field includes confidence score for data accuracy.
Users can review and edit any pre-filled information before submission.
Generate supporting documentation (income summary, expense breakdown) automatically.
Aggregate data from multiple accounts for complete financial picture.
A loan marketplace uses prefill to reduce application completion time.
Result: Application time reduced from 28 minutes to 4 minutes, conversion up 55%.
A broker platform pre-fills mortgage applications with verified financial data.
Result: Application accuracy improved by 85%, reducing bank decline rates.
A business lender prefills applications using business banking transaction data.
Result: Approval time reduced from 7 days to 2 days with verified data upfront.
POST /loan-application/prefillGET /accounts/{accountId}/application-dataPOST /application-data/extractGET /prefill/{sessionId}/dataPersonal details
Employment information
Income sources
Expense breakdown
Existing commitments
Assets and liabilities
OAuth 2.0 / CDR consent
Yes
Name, address, employer, income, expenses, existing loans, rent/mortgage payments, and financial commitments can typically be extracted.
Extraction accuracy is typically 90-95% for structured fields like income. Each field includes confidence score.
Yes, all pre-filled data is editable. Users should review and confirm accuracy before submission.
The API indicates which fields were successfully extracted and which require manual entry.
Yes, prefill works for personal loans, mortgages, business loans, and other complex applications.
Customers typically complete prefilled applications 75-85% faster than manual entry.
Yes, data extracted from CDR-authorized banking connections is verified and compliant for lending use.
Fintech
Enable users to connect and view all their bank accounts in one place. Fiskil's account aggregation API provides real-time access to accounts, balances, and transactions from 100+ Australian banks.
Lending
Verify applicant income instantly using real bank transaction data. Fiskil's income verification API reduces loan processing time and improves accuracy.
Lending
Calculate loan affordability using real cash flow data. Ensure responsible lending with automated affordability checks based on income, expenses, and existing commitments.
Join hundreds of companies using Fiskil to power their lending applications. Get started today with our developer-friendly API.
Products
© Fiskil 2026. All rights reserved.