Atomara
Atomara
Atomara
Atomara is a forensic PDF verification API that checks bank statements and other borrower documents for signs of editing after issuance, returning a verdict, authenticity score, and evidence-backed findings from the file's own structure, metadata, fonts, and balance math.
Atomara is a forensic PDF verification API that checks bank statements and other borrower documents for signs of editing after issuance, returning a verdict, authenticity score, and evidence-backed findings from the file's own structure, metadata, fonts, and balance math.

Overview
Atomara checks whether a PDF was edited after the issuer wrote it. Lenders and platforms send a bank statement, payslip, invoice, or similar file over a REST API and get back JSON with a verdict, a 0 to 100 authenticity score, and every forensic signal the engine found, including the page and area where it appears. The engine reads the file itself: generator and editor fingerprints, incremental save history, font and layout consistency, digital signatures, and whether statement figures add up line by line. It is issuer-agnostic by design, so there is no bank-template list to wait for, and when the method cannot tell it returns inconclusive rather than guessing. The same result is available in the Atomara dashboard for the person reviewing a flagged application. Digital PDFs carry the full check; scans and photos of paper documents are accepted but do not receive a structural authenticity score.
Use Cases
Screen borrower-submitted bank statements for editor fingerprints, altered figures, and save-history anomalies before underwriting uses the numbers.
Call a REST endpoint from an origination or decisioning workflow and branch on verdict, score, and stable signal ids in the JSON response.
Flag payslips, invoices, receipts, and employment letters that show post-issuance editing traces alongside lending KYC and onboarding files.
Give credit reviewers the same evidence-backed report the API returns, including where on the page each finding sits.
Overview
Atomara checks whether a PDF was edited after the issuer wrote it. Lenders and platforms send a bank statement, payslip, invoice, or similar file over a REST API and get back JSON with a verdict, a 0 to 100 authenticity score, and every forensic signal the engine found, including the page and area where it appears. The engine reads the file itself: generator and editor fingerprints, incremental save history, font and layout consistency, digital signatures, and whether statement figures add up line by line. It is issuer-agnostic by design, so there is no bank-template list to wait for, and when the method cannot tell it returns inconclusive rather than guessing. The same result is available in the Atomara dashboard for the person reviewing a flagged application. Digital PDFs carry the full check; scans and photos of paper documents are accepted but do not receive a structural authenticity score.
Use Cases
Screen borrower-submitted bank statements for editor fingerprints, altered figures, and save-history anomalies before underwriting uses the numbers.
Call a REST endpoint from an origination or decisioning workflow and branch on verdict, score, and stable signal ids in the JSON response.
Flag payslips, invoices, receipts, and employment letters that show post-issuance editing traces alongside lending KYC and onboarding files.
Give credit reviewers the same evidence-backed report the API returns, including where on the page each finding sits.

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© 2026 LendAPI, Inc. All rights reserved.
LendAPI
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© 2026 LendAPI, Inc. All rights reserved.
LendAPI
Solutions
© 2026 LendAPI, Inc. All rights reserved.
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