Automated data extraction
Automatically extracts structured fields from bank statements, reducing the need for manual transcription and review.
AZAPI.ai’s Bank Statement Analyzer API extracts and structures data from bank statements in PDFs, images, and scans. It is aimed at financial teams that need faster loan processing, onboarding, and statement review.
Bank Statement Analyzer API Solution is an AZAPI.ai product for extracting and structuring financial data from bank statements. It is designed to replace manual data entry with automated parsing so teams can work with statement data in a more consistent format.
The product is presented for digital banking and adjacent financial workflows, including loan processing, customer onboarding, credit risk review, and financial analysis. AZAPI.ai says the API can process bank statements in formats such as PDFs, images, and scanned documents, and turn them into usable fields and transaction-level insights.
Automatically extracts structured fields from bank statements, reducing the need for manual transcription and review.
Processes PDF, JPG, PNG, and scanned files, which helps teams handle mixed input sources without separate tooling.
Organizes transaction data into categories such as expenses, income, and loans to make statement review easier.
Flags suspicious transactions and unusual patterns to support review and risk analysis workflows.
Makes extracted information available quickly so teams can move from document intake to decision-making with less delay.
Use the API to extract income, expenses, cash flow, and transaction details during loan intake so reviewers can work from structured records instead of manual statement reading.
Apply the analyzer during KYC or account-opening flows to turn uploaded statements into readable data for faster customer verification.
Use transaction categorization and anomaly detection to support credit assessment and broader financial risk review.
Give accounting and audit teams a faster way to organize statement activity for reconciliation, reporting, and document review.
Help fintech and banking teams process large volumes of statements consistently when they need automated document handling rather than manual entry.
The page describes it as an API that extracts, analyzes, and structures bank-statement data automatically from PDFs, images, and scanned documents. It is positioned for businesses that want to reduce manual review in financial workflows.
The product page says it can extract account holder names, account numbers, transaction details, balance summaries, and debit/credit entries. It also mentions AI-powered categorization and real-time processing.
The source pages do not provide a dedicated setup guide, but they state that the API is designed for easy integration into existing systems and web applications. The recommended approach is to test the integration and validate the workflow in your own environment.
The product is presented for fintech companies, NBFCs, financial institutions, lenders, accounting firms, and similar teams that need structured financial data from statements. It is not described as a consumer-only tool.
The pricing page shows AZAPI.ai uses a credit-based pricing model across OCR and CAPTCHA services, but it does not list a bank-statement-specific plan or price. A free trial is promoted on the site.
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