# White-label bank statement parsing for your product

> Put a production bank statement parser inside your own product under your own brand. White-label API, your domain, your pricing, volume-based licensing — no extraction team required.

Source: https://parsemystatement.com/white-label
Updated: 2026-09-17

If your product needs bank statement parsing but building an extraction team is not the business you are in, you can run mine under your own brand. A production engine with real, published accuracy benchmarks, exposed through your domain, priced for volume, with the option to move fully inside your infrastructure later.

**At a glance**

- Your brand, your domain, your pricing — the engine is invisible to your users
- Live in weeks, not the two quarters an in-house build takes
- Accuracy backed by a published ground-truth benchmark, not a datasheet claim
- Upgrade path to a full source licence or on-premise deployment

## Who this is for

Accounting and bookkeeping platforms whose users arrive with a folder of PDF statements. Lending and underwriting products that need transaction history from documents rather than an open-banking connection. Personal finance apps in markets where aggregation coverage is poor. Expense and audit tools that receive statements as attachments. Agencies delivering finance automation to clients.

What these have in common: statement parsing is necessary but it is not your differentiator. Users judge you on underwriting quality, or reconciliation UX, or advisory value — not on how well you handle a two-column HSBC PDF. Meanwhile building it properly takes a specialist team six months and never stops needing maintenance, because every bank redesigns its statement layout eventually.

White-labelling turns that from a hiring problem into a line item.

## What you get

### Your brand end to end

API served from your domain, your naming in every response, your documentation. Nothing in the integration surface identifies the underlying engine to your users.

### Production API

Async upload, status polling, and result fetch. Normalized transactions as JSON, CSV, or XLSX, with typed dates, signed amounts, references, merchant classification, and per-transaction page attribution.

### Built-in validation

Every conversion is balance-checked — opening plus credits minus debits equals closing — and flagged when it fails, so your product can surface uncertainty instead of silently passing bad data to a lender or a ledger.

### MCP server included

The same pipeline exposed as an MCP server, so AI agents built on your platform can call it directly. Increasingly this is what enterprise buyers ask about first.

### Volume pricing

Per-page tiers that fall as you grow, with a committed-volume option. You set your own end-user pricing and keep the margin.

### Direct engineering access

You talk to the person who wrote the parser. New bank layouts, schema additions, and integration problems are handled by the engineer, not a support tier.

## How onboarding works

### 1. Accuracy trial

Send a representative sample of the statements your users actually upload. I run them through the engine and give you scored results, including the failures, so you evaluate on evidence rather than on a demo I curated.

### 2. Commercial terms

Volume tiers, branding scope, support response times, and data-handling terms agreed. NDA and DPA signed.

### 3. Integration

Keys issued, endpoints pointed at your domain, and integration support while your team builds against the API. Typically one to three weeks of your engineering time.

### 4. Layout coverage

Banks that your users submit and the engine handles poorly get added as profiles. This is continuous work included in the relationship, not a change request.

### 5. Scale or bring it in-house

As volume grows you either stay on the API, move to a deployment inside your own infrastructure, or take a full source licence. All three paths are open and priced.

## Ways to run it

| Model | What it means | Best when |
| --- | --- | --- |
| Hosted white-label API | I operate it; your brand and domain in front | Fastest launch, no infrastructure to own |
| Dedicated instance | Isolated deployment, your region, your retention policy | Data-residency requirements or high volume |
| Deployed in your cloud | Runs inside your VPC under licence | Documents may not reach a third-party processor |
| Full source licence | You own and modify the code | Extraction becomes core to your product |

## Indicative commercial terms

Final pricing depends on volume, branding scope, and support level. These are starting points for the conversation, not a rate card.

### Launch — from $750 / month (Live in 2–4 weeks)

For products validating statement parsing with early volume.

- Hosted white-label API on your domain
- Per-page volume tiers
- CSV, XLSX, and JSON outputs
- Email support with a business-day response
- Accuracy trial on your statements before you commit

### Scale — Custom (Live in 3–6 weeks)

For products where statement parsing is on the critical path.

- Everything in Launch
- Dedicated instance and region of your choice
- Committed volume pricing
- Prioritised bank-layout coverage
- Named engineering contact and an agreed SLA

### In your infrastructure — Custom (6–10 weeks)

The engine deployed inside your own cloud or datacentre under licence.

- Runs entirely within your perimeter
- Annual licence plus deployment engagement
- Compliance and data-flow documentation
- Upgrade path to a full source licence

## Frequently asked questions

### Will our users know the parsing is not ours?

No. The API is served from your domain under your naming, responses carry no third-party branding, and the documentation is yours. Attribution requirements, if any, are agreed in the contract rather than baked into the product.

### Which banks are supported?

The engine is layout-general rather than a fixed list of integrations — it reads statement structure rather than matching per-bank templates, so unfamiliar banks usually work on first contact. Bank-specific profiles then improve accuracy where a layout is unusual. The accuracy trial on your own statements tells you exactly where you stand before you sign anything.

### What happens to documents you process?

On the hosted service, documents and outputs are deleted automatically within 24 hours, and retention can be shortened for your account. A DPA is signed as standard. If your requirements do not allow third-party processing at all, the in-your-infrastructure model exists for exactly that.

### What if we outgrow the API?

Then you move — to a dedicated instance, a deployment in your own cloud, or a full source licence. The migration path is deliberate, because a white-label arrangement that traps you is a bad deal you would eventually leave anyway.

### Can we get an exclusivity arrangement?

Category or geographic exclusivity can be discussed for committed-volume agreements. It is priced accordingly, since it forecloses other business.

### How is this different from building it ourselves?

Time and ongoing cost, mostly. A capable team can build a first version in a few months; what surprises people is that extraction accuracy is permanent maintenance, not a project — layouts change, models change, and the evaluation harness needs feeding forever. If extraction is genuinely core to your product, build it, and hire me to help you do it properly. If it is not, license it.

## Test it on your own statements first

Send a representative sample — including the ones that break other parsers. You get scored results with the failures included, before any commercial conversation.

Contact: adarsh@parsemystatement.com · https://parsemystatement.com/contact

## Related

- https://parsemystatement.com/licensing
- https://parsemystatement.com/enterprise
- https://parsemystatement.com/services/document-data-extraction
- https://parsemystatement.com/services/custom-ocr-development