Dext, Nanonets and Ocrolus Alternatives: Three Jobs

Dext, Nanonets and Ocrolus alternatives: what each tool is actually for

People arrive here looking for a Dext alternative, a Nanonets alternative or an Ocrolus alternative, and usually because what they need is a bank statement converter that a lender can check. Four products get compared in one breath because they all touch a bank statement. They are answering different questions for different people, and choosing badly is usually a mismatch of reader rather than of accuracy.

Updated 29 October 2026 · 8 min read

The names in this category get used as if they were interchangeable. They are not. One is a bookkeeping capture tool, one is a general document automation platform, one is built for lending operations at volume, and one reads a statement for an analyst who has to defend a decision. The question worth asking is not which is most accurate, but who is going to read the output.

Three jobs that get called “statement automation”

Bookkeeping capture turns documents into entries in accounting software, and is judged on how little a bookkeeper has to retype. General document AI turns any configured document into structured fields, and is judged on how many document types it can be taught. Lending-grade statement processing turns a borrower's statements into transaction data a credit model can use, and is judged on whether the numbers reconcile.

Bank statement tools compared by who reads the output
	Dext	Nanonets	Ocrolus	SheetParser
Who it is built for	Bookkeepers and accounting practices.	Operations teams with many document types.	Lenders and credit teams.	Credit analysts reading statements for a lending decision.
What it does with a statement	Captures it, codes it, publishes it into accounting software.	Extracts the fields you configure, generally.	Reads statements and produces lending-grade transaction data.	Reads the statement into a spreadsheet with the arithmetic reconciled.
Client or practice structure	Yes: clients, teams, dashboards.	Workflow and integrations by configuration.	Yes, built for lending operations at volume.	No. One file at a time, no client structure.
Arithmetic reconciliation	Not its stated purpose.	Not by default.	Yes, as part of a lending pipeline.	Yes: opening plus transactions equals closing, and month to month.
Where the record lives	In the tool, with the documents.	In the tool or your systems.	In the lending platform.	In your spreadsheet and your loan file. We keep no archive.

What we do not do

No client or practice structure. No dashboards, no teams, no per-client memory. If you are an accountant managing eighty client files, that structure is the product and we do not have it.
No configurable field extraction. We read a statement; we do not read arbitrary forms because you defined the fields.
No decisioning, scoring or audit workflow. We produce a reconciled file, not a credit opinion, and we do not replace a lending platform.
No archive. We are not where the documents live. The loan file and your systems hold the record; read the privacy page for what is retained during processing.

When one of the others is the better choice

You are a bookkeeping practice. Dext, or an equivalent, because the client structure and coding rules are the work.
Your documents are mixed and change weekly. A general platform, because you can configure each new document type rather than wait for a product.
You process lending files at volume with a compliance function. A lending platform, because the audit trail and the integrations are the requirement.
You are an analyst with a file to read this afternoon. The narrow tool. There is nothing to configure and nothing to onboard.

What a lender actually needs from a statement file

Not extraction. Reconciliation. A credit analyst can read a transaction list; what they cannot do is prove, months later, that the list is complete. The checks that make a file defensible are mechanical: the opening balance plus every transaction must equal the closing balance printed on the statement, the closing balance of one month must equal the opening balance of the next, and the period covered must be the period requested.

The fourth thing is provenance. Every figure should trace back to a page and a line of the borrower's own statement, so that when a deposit is questioned the answer is a page number rather than a recollection. That is the difference between a number an analyst asserts and a number an analyst can show.

The practical workflow

Collect every account and every month requested, and note what is missing before you start.
Read the statements into a spreadsheet with the transactions and balances intact.
Run the three checks: month arithmetic, month-to-month continuity, period coverage.
Read the deposits the decision turns on, and keep the page reference beside each one.
Export to the model or to the books, and keep the reconciled file with the loan file.

The tools differ in how much of that they do for you and how much they expect you to bring. What none of them can do is know your credit policy, which is why the last word on any of these numbers is still an analyst's.

Common questions

Is SheetParser an alternative to Ocrolus?+

For one job, yes: turning a borrower's bank statements into a spreadsheet a credit analyst can check line by line, with every total reconciled to the statement's own opening and closing balance. It is not an alternative to a full lending platform, and it does not do the decision, the scorecard or the audit trail a regulated lender may be required to keep.

Is it an alternative to Dext?+

Only for the reading step. Dext is built for bookkeepers and accountants: capture at scale, coding rules per supplier, client dashboards and a document archive. SheetParser reads bank statements for a different reader, a credit analyst looking at deposits and balances, and it has no client structure and no archive.

Is it an alternative to Nanonets?+

Nanonets is general document automation: you define the fields, it extracts them from invoices, receipts, forms and statements. SheetParser is not configurable that way. It knows one document shape well, the statement, and it reconciles the arithmetic rather than extracting whatever fields you configure.

What should a lender check on an extracted statement?+

Three things: that the opening balance plus every transaction equals the closing balance, that the closing balance of one month equals the opening balance of the next, and that the period covered is the period requested. A file that passes those three is far more likely to be usable in a credit decision.

Why does provenance matter in underwriting?+

Because a declined or approved loan can be questioned. If a deposit figure cannot be traced back to a page and a line in the borrower's statement, the analyst has no way to defend it. A number with no page reference is an assertion; a number with one is evidence.

Can I use these tools together?+

In principle, and often sensibly: one tool to capture documents, another for the underwriting view. The practical risk is a second system of record, where two tools hold different versions of the same month. Whichever you choose, decide which copy is authoritative before the first loan file.