Bank Statement Extract
Extract transaction data into structured JSON for analysis
- Transaction-level structured data
- Categories and running balances
- Ready for reconciliation workflows
Bank Statement Extract
Available as an action in
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Automate in 3 Steps
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Statement → Accounting software
Bank PDF → Reconciliation
Quarterly statements → Audit trail
For Developers
Get started in seconds. Copy and run.
import { createClient } from "@pdfvector/client";const client = createClient({ apiKey: "YOUR_API_KEY" });const result = await client.bankStatement.extract( { url: "https://example.com/monthly-statement.pdf", prompt: "Extract account holder, opening balance, closing balance, statement period, and all transactions", schema: { type: "object", properties: { accountHolder: { type: "string" }, openingBalance: { type: "number" }, closingBalance: { type: "number" }, statementPeriod: { type: "string" }, transactions: { type: "array", items: { type: "object", properties: { date: { type: "string" }, description: { type: "string" }, amount: { type: "number" }, balance: { type: "number" }, }, }, }, }, }, model: "max", }, { context: { documentId: "stmt-nov-2024" } },);console.log(result.data);Key Features
Transaction Schema
Define a custom schema to extract dates, descriptions, amounts, and categories for each transaction.
Category Detection
AI categorizes transactions into types like deposits, withdrawals, fees, and transfers.
Export-Ready
Structured output is ready for import into accounting tools, spreadsheets, or databases.
Credit Costs
Pick the model tier that fits your use case
Nano
Basic field extraction from simple text documents. Fastest response.
Mini
Reliable extraction from documents with tables and nested structures.
Pro
Accurate extraction from complex layouts, forms, and scanned documents.
Max
Highest accuracy for large documents with complex schemas and nested data.
Everything You Need for Document Processing
Parse, ask questions, and extract structured data from any document type
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