Documentric's PDF data extractor turns bank statement PDFs into structured, editable transactions with 99% accuracy in under 30 seconds, then hands that data to five purpose-built features: OCR extraction, balance reconciliation, transaction categorization, financial analysis, and fraud-ready exports.
10 free pages a month once you sign up · No credit card required
Every feature below runs on the same AI extraction engine, so you upload one PDF once and get accurate data across QuickBooks Online, Xero, Sage, Quicken, and Excel without re-entering a single row. Whether you are a CPA closing monthly books, a mortgage broker verifying income, a bookkeeper reconciling client statements, or a financial investigator building a transaction timeline, this page explains exactly how each Documentric feature works, who it is built for, and how it compares to DocuClipper and MoneyThumb. Documentric reads statements from Chase, Bank of America, Wells Fargo, HSBC, Barclays, and more than 10,000 other banks worldwide, with no bank-specific templates to configure. The processing cost behind every feature stays close to $0.003 per page, which is why the free tier can let you convert without asking for an account or a credit card, and why the Starter, Professional, and Business plans below can price by page volume instead of by seat or by feature.
99% accurate extraction from digital and scanned PDFs, from any of 10,000+ banks worldwide.
Every extracted statement is auto-checked against its printed opening and closing balance.
AI payee matching and QuickBooks category mapping. Coming to Professional and Business plans.
Income detection, recurring expense tracking, and cash flow summaries from extracted data.
Exact amounts, timestamps, and merchant names, extracted verbatim for investigators.
These five features are not five separate products. They are one pipeline. A PDF comes in, OCR reads it, reconciliation checks the math, categorization tags each row, analysis summarizes the patterns, and the result is available to fraud investigators or auditors as a clean export. An accountant handling 10 client statements averaging 20 pages each uses 200 pages in a single batch, well inside the Starter plan's 300-page monthly allowance, and every one of those 200 pages passes through the same five steps automatically. You only review and confirm the output; you do not re-run each feature manually.
Bank statement OCR is the technology underneath every Documentric feature. When you upload a PDF, Documentric first checks whether the file has a digital text layer, the kind you download directly from an online banking portal, or whether it is a scanned image: a photocopy, fax, or phone photo of a paper statement. Digital PDFs are read directly, giving 99% extraction accuracy. Scanned PDFs run through an OCR pipeline that corrects page rotation, detects multi-column layouts, and reads faint or low-resolution text, typically reaching above 97% accuracy on clean scans.
This is where ai document extraction goes beyond older OCR tools. Instead of matching a fixed template per bank, Documentric's ai data extraction engine understands the layout of a table: which column holds the date, which holds the debit or credit amount, and which holds the running balance, even when two banks format that table completely differently. That is also why document extraction ai handles more banks than template-based competitors like MoneyThumb, which relies on hand-built templates that break when a bank redesigns its statement layout.
Once extraction finishes, every row lands in a side-by-side review table next to the original PDF, so you can confirm accuracy before exporting. Read the full breakdown, including how Documentric handles password-protected files and non-English currency symbols, on the bank statement OCR page, or see the underlying conversion mechanics on the bank statement converter solutions page.
As a pdf data extraction software built to handle messy, real-world PDFs, Documentric does not stop at reading rows and columns. The categorization layer takes each extracted transaction description, for example "AMZN*MKT 1234567", normalizes it to a recognizable payee ("Amazon.com"), then maps that payee to a QuickBooks expense account such as Computer and Internet Expenses or Meals and Entertainment.
Automatic AI categorization, this ai powered data extraction step, is scheduled for the Professional and Business plans in the second half of 2026. Every plan, including the free tier and Starter at $19/month, already includes a manual category editor in the review table, plus per-payee rules that persist across every future upload once automatic categorization launches. Categorized transactions carry the correct QuickBooks account name when exported as a QBO file, so nothing needs re-categorizing after import.
For bookkeepers managing several clients, this turns a recurring manual task, tagging the same vendors month after month, into a one-time rule. See the full roadmap and supported category list on the transaction categorization page.
Every statement processed by Documentric passes through built-in account reconciliation software before you ever see an export button. After extraction, Documentric sums every debit and credit and checks the result against the opening and closing balance printed on the statement. If a row was missed during OCR, duplicated across a page break, or misread, a "3" extracted as an "8", for example, the mismatch shows up immediately as a flagged banner with the exact dollar difference.
Automated bank reconciliation like this exists because OCR, even at 99% accuracy, is not perfect, and a single wrong digit in a bank statement can throw off an entire month of bookkeeping. Rather than trusting the extraction blindly, Documentric functions as transaction reconciliation software first: no PDF exports to QBO or CSV until the numbers add up, or until you have manually reviewed and accepted the discrepancy.
This works across every bank format without configuration. Chase, Wells Fargo, Bank of America, HSBC, and Barclays statements are all reconciled the same way, reading the opening and closing balance directly from the header or footer regardless of layout. See exactly how mismatches are flagged and fixed on the reconciliation page.
If your end goal is to reconcile QuickBooks against a pile of PDF statements, Documentric's QBO export is built for exactly that. Every transaction that passes the balance check above exports as a properly formatted OFX 2.1.1 file that QuickBooks Online reads natively, with dates, descriptions, and amounts already matched to the statement.
Traditional quickbooks bank reconciliation means manually keying in transactions or connecting a live bank feed that many small businesses cannot access, particularly for older statements, closed accounts, or clients who bank with institutions outside the major live-feed networks. Documentric skips that limitation entirely. Upload the PDF, review the extracted rows next to the original statement, and export a QBO file that lands directly in the QuickBooks reconciliation workflow.
This also works for Xero and Sage. Xero accepts the same structured export in CSV format, and Sage 50 users can import the CSV export directly into their bank reconciliation module. Quicken users get a compatible CSV as well. See supported formats on the QuickBooks integration page.
Once transactions are extracted and reconciled, Documentric becomes one of the more practical tools for financial analysis available to accountants and lenders working from PDF statements rather than live bank feeds. The analysis of financial statements starts automatically: recurring deposits are separated from one-off credits to identify real income sources, regular monthly debits are flagged as fixed costs, and total inflows versus outflows are summarized by month.
Because every transaction is tagged with a date, description, and amount, exported data supports standard financial statement analysis ratios, such as average monthly cash flow, expense-to-income ratio, or largest single-month outflow, calculated in Excel or Google Sheets after export. Large transaction flagging highlights any deposit or withdrawal above a threshold you set, useful for spotting a single large income event during mortgage underwriting or an unusual transfer during a financial investigation.
Merchant frequency analysis aggregates spend by payee across the full statement history, so a bookkeeper can generate a financial analysis report showing the top ten vendors by dollar volume in a few clicks rather than a few hours. As a bank statement analyzer, Documentric does not just extract, it structures the data so month-over-month comparisons and vendor trend reports are already possible the moment the export lands in Excel. Full detail on income detection and cash flow summaries is on the financial analysis page.
Documentric is not fraud detection software in the sense of an automated scoring engine like FICO or Actimize. What it provides instead is the foundation every fraud investigation needs: exact transaction amounts, timestamps, merchant names, and running balances extracted verbatim from the original PDF, with nothing summarized or altered.
Purpose-built fraud detection tools apply rules engines and risk scores at the transaction-monitoring layer, a different function from document extraction. Documentric's role is upstream of that: converting a stack of PDF bank statements, sometimes from five different banks in a single case, into one consistent, sortable, exportable dataset. Investigators can then apply their own fraud prevention software, spreadsheet formulas, or forensic tools such as IDEA and ACL on top of clean data instead of re-typing numbers from scanned pages.
This matters for family law financial discovery, insurance claims investigation, and internal audits of employee expense accounts, where the original PDF remains the document of record and the structured export is a derivative analytical tool. Every extracted row, including merchant names exactly as printed, stays intact for that reason. Full detail on what is and is not included is on the fraud detection page.
Every feature above ends the same way: an export. Documentric lets you convert bank statement to excel (.xlsx), generate a QuickBooks-ready QBO file, or download a plain CSV, all from the same reviewed transaction table. There is no separate tool or re-upload required to switch formats.
A pdf bank statement to excel export is the most common choice for financial analysis, pivot tables, and merchant frequency reports, since Excel and Google Sheets both open the .xlsx file directly with correct data types on dates and amounts. As a bank statement to csv converter, Documentric also supports Xero, Sage, Quicken, and any accounting tool that accepts a plain CSV import, so the same extracted data can feed more than one destination without re-processing the PDF.
Pricing is based on pages, not exports: the free tier needs no account to try and gives you 10 pages a month once you sign in, Starter is $19 per month for 300 pages, Professional is $49 per month for 900 pages, and Business is $129 per month for 2,500 pages. Extra pages on any paid plan cost $0.10 each and appear on your next invoice, so a busy month is never blocked. See the full breakdown, including page-based examples for accountants processing multiple client statements per month, on the pricing page, or bank-specific conversion guides for Chase, Wells Fargo, and hundreds of other banks on the convert hub.
Every feature on this page starts the same way, with a single PDF upload. First, drop in a bank statement, digital or scanned, from any bank. Second, watch the extraction finish in under 30 seconds and check the results against the original PDF, which stays visible side by side with the transaction table for the entire session. Third, resolve any reconciliation flag inline, adjust a category if needed, and export to QBO, CSV, or Excel.
No installation is required, and nothing needs to be configured before the first upload. A one-page test statement takes about the same 30 seconds as a multi-page batch, since each page is processed independently, which makes it practical to try every feature on a single real statement before committing to a paid plan.
Every feature described above is included in every Documentric plan except automatic categorization, which is plan-gated. Here is how the full feature set and pricing compares to the two most-searched alternatives.
| Feature | Documentric | DocuClipper | MoneyThumb |
|---|---|---|---|
| Free tier | Yes, no account needed | None | None |
| Starter plan | $19/mo (300 pages) | $39 to $159/mo | $29 to $99/mo |
| OCR accuracy | 99% (digital), 97% (scans) | ~95% | ~93% |
| Balance reconciliation | Automatic, before export | Not included | Manual only |
| Transaction categorization | Manual now, AI in H2 2026 | Not included | Not included |
| Banks supported | 10,000+ | 500+ | US banks only |
| Export formats | QBO, CSV, Excel | CSV, PDF | CSV |
Documentric's OCR runs on LlamaParse at roughly $0.003 per page, about 100x cheaper than the per-page cost most competitors pass on through their pricing tiers, which is part of why the free tier needs no account at all. At $19 for 300 pages, Starter works out to about $0.06 per page against roughly $0.20 per page on DocuClipper's $39, 200-page plan: three times cheaper per page.
Documentric is built for anyone who regularly receives PDF bank statements from clients, borrowers, or counterparties rather than pulling data from a live bank feed. Five distinct roles rely on a different combination of the features above, from OCR alone to the full pipeline including reconciliation and categorization, but every one of them starts from the same free tier, no account required, before deciding whether Starter, Professional, or Business fits their monthly page volume.
Close monthly books faster by converting a full year of client PDF statements to reconciled QuickBooks and Xero data in minutes instead of days of manual entry.
Verify extracted transactions against the original PDF before entering anything into a client ledger, then reuse per-payee categorization rules across every future upload.
Turn a drawer of PDF bank statements into a clean Excel export for tax prep, budgeting, or handing off to an accountant, without a QuickBooks subscription.
Verify 2 to 3 months of income and reserves from borrower-submitted PDFs, with every deposit accounted for by the reconciliation check before the file goes to underwriting.
Build a transaction timeline across statements from multiple banks for discovery or fraud investigation, using data extracted verbatim from the original PDF exhibit.
For PDF statements specifically, Documentric functions as account reconciliation software built into the extraction step itself: every statement is auto-checked against its printed opening and closing balance before export. General ledger tools like QuickBooks and Xero handle reconciliation once the data is already inside the software, but Documentric catches OCR errors before that data ever arrives.
Yes. Once transactions are extracted, Documentric identifies recurring income deposits, flags regular monthly debits as fixed costs, and summarizes cash flow by month, which are the core inputs lenders and CPAs need for an analysis of financial statements during underwriting or year-end review. Mortgage brokers commonly use this to confirm 2 to 3 months of reserves before a loan file moves to underwriting, without re-typing a single deposit.
Yes. Every extracted and reconciled statement can be exported as a bank statement pdf to csv file, alongside QBO for QuickBooks Online and .xlsx for Excel or Google Sheets. All three export formats come from the same reviewed transaction table, with no re-upload needed.
Automatic AI categorization is scheduled for the Professional and Business plans in the second half of 2026. Every plan, including the free tier and the $19/mo Starter plan, already includes a manual category editor with persistent per-payee rules in the review table.
No. Documentric does not score transactions for fraud risk or run a rules engine, unlike purpose-built fraud detection tools such as FICO or Actimize. It extracts exact amounts, dates, and merchant names verbatim from PDF bank statements so investigators can apply their own analysis on clean, structured data.
The free plan includes OCR extraction, balance reconciliation, manual categorization, and income and cash flow analysis. You can try it with no account at all, and signing in gives you 10 free pages a month, with a 15-page limit per document. Starter ($19/mo, 300 pages), Professional ($49/mo, 900 pages), and Business ($129/mo, 2,500 pages) unlock the same feature set at higher volume, so a growing practice can scale up without switching tools or re-learning a new interface.
Digital PDFs downloaded from a bank portal extract at 99% accuracy. Scanned or faxed statements run through an OCR pipeline that corrects rotation and reads low-resolution text, typically exceeding 97% accuracy on clean scans. Every row is shown next to the original PDF for a quick visual check before export.
No. To reconcile QuickBooks against PDF statements, Documentric exports an OFX-format QBO file with dates, descriptions, and amounts already matched, so accounts without a live bank feed, including closed accounts or smaller institutions, still import cleanly into QuickBooks Online.