AI Substantive Testing | Audit Evidence

Substantive Testing

Review

Every Transaction

Automate evidence testing - Retreive information from the supporting document and verify against underlying transaction.

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Execution Challenges

Transactions Are Digital.

Testing Remains Manual.

Manual document verification and documentation increases fieldwork time and the risk of missed discrepancies.

Automated Execution

Transform Manual Testing Into

Structured Automation

AI Execution

Automated Evidence Testing

Retrieve information from documents and verify against undelying transaction - eliminating manual review.

Intelligent evidence matching

Transaction level traceability

Structured exception reporting

Audit trail integrity

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Table showing a preview of invoice extraction with columns for Invoice #, Date, Amount, Vendor Name, and PO#. Example entries include INV-1001 dated 2025/01/06 for $15,300 from Studio Shop.

Table comparing Input and Output dollar amounts with a Difference column showing $300, $0, $346, $0, $0, $0, $1,690, $4,150, and $0 differences highlighted in red, green, and blue backgrounds.

Instant validation

Catch Errors Effortlessly

Evidence Variance

Instantly compare ledger amounts against extracted document values.

Exception Highlighting

Flag mismatches clearly for rapid auditor review.

Discrepancy Detection

Identify calculation gaps across linked transaction fields.

Reviewer Controls

Override findings with traceable approval history.

Universal File Processing

Extract Structured Data

Fins AI agents capture transaction level data from unstructured files to support automated substantive testing workflows.

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Multi Format Support

Process PDFs, images and other unstructured data layouts.

Context Aware Extraction

Retain context of financial tables and nested disclosures.

User interface displaying a three-step process with tabs labeled Input, Source, and Rules; showing output columns settings for Invoice # with Verify operation and Hash data type, and Date with Verify operation and Date data type, each having result placement options.

Execution Features

Capabilities Powering

Substantive Testing

Precision Field Extraction

Extract structured financial values from invoices, ledgers, and statements with contextual accuracy.

Intelligent Data Matching

Automatically match transactions, OCR results, and supporting documents using structured validation logic.

Context Aware Validation

Interpret financial fields based on transaction type, audit standards, and supporting documentation context.

Source Linked Evidence

Connect every tested value directly to its originating document with full traceability.

Traceable Annotations Layer

Record findings, highlights, and reviewer notes with immutable source-level references.

Collaborative Review Controls

Enable auditors to comment, validate exceptions, and finalize testing conclusions together.

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Risk Assessment

Risk scoring at transaction level with ML

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Financial Statement Validation

Review Financial Statments for sign off readiness

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