Upload any bank statement PDF. AI extracts, categorizes, and structures every transaction for reconciliation, expense analysis, income verification, and more.
No account needed · No credit card · Works with any bank
Structured transaction data unlocks a range of analysis workflows — whether you are an accountant, lender, or investigator.
Match extracted transactions against your general ledger. Documentric auto-verifies balances so discrepancies surface before you import.
Automatically tag transactions by category — payroll, rent, utilities, travel — to accelerate month-end expense reporting.
Identify recurring income credits quickly. Useful for mortgage applications, loan assessments, and financial due diligence.
Drop any bank statement PDF — from any bank, any country. Digital and scanned formats are both supported.
Every transaction is extracted, parsed into date, description, amount, and category fields, and displayed in a reviewable table.
Download structured CSV or Excel output. Use it in your own tools, share with clients, or feed into reporting workflows.
Machine learning models identify every transaction row in a PDF — even from complex multi-column layouts and scanned images.
Each transaction is broken into structured fields: date, merchant/payee name, debit/credit amount, and running balance.
Documentric checks that the sum of extracted transactions matches the opening and closing balance printed on the statement.
Transactions are automatically tagged with spending categories (groceries, utilities, payroll, rent, etc.) based on merchant name patterns.
Export all extracted transactions as a clean CSV — ready for Excel, Google Sheets, Xero, Sage, or any BI tool you use.
All uploaded files are automatically deleted within 24 hours. Your clients' financial data is never stored longer than necessary.
Eliminate manual data entry. Extract transactions from client statements in seconds and import directly into your practice management or accounting software.
Accountant solution →Verify income and spending patterns quickly. Pull structured transaction data for affordability assessments without manual review of every page.
Lender solution →Produce a structured, auditable transaction record from bank statements for use as evidence in financial disclosure proceedings.
Professional solution →Rapidly extract and cross-reference transactions across multiple statements and accounts. Export to a single spreadsheet for pattern analysis.
Investigator use case →Documentric extracts every transaction row: transaction date, description or merchant name, debit amount, credit amount, and running balance. It also detects the statement period, account number (where present), and opening/closing balances.
Yes. There are no bank-specific templates to configure. Documentric's AI adapts to any PDF layout — whether it's a Chase checking account, an HSBC business account, or a regional credit union statement.
Documentric uses merchant name patterns and transaction descriptions to assign spending categories. Categories include groceries, utilities, payroll, rent, travel, entertainment, and more. You can review and edit category assignments in the inline table before export.
Yes. With a paid plan you can upload multiple statements and export a combined CSV covering all transactions across all files. This is useful for accountants and lenders who need to analyze several months or accounts at once.
Documentric achieves 99% extraction accuracy on well-formatted PDFs. Every extraction includes an inline review step where you can verify and correct any transaction before export — producing a clean, auditable record suitable for professional use.