AI Automation for Audit & Compliance

Most accounting firms use platforms like AuditBoard or Workiva to manage audit workflows. These tools are excellent for documentation and control tracking but do not automate the evidence analysis itself. An auditor still manually samples transactions, pulls supporting documents from a separate system, and visually confirms details. The platform provides the checklist, but the tedious, error-prone checking remains a manual task that consumes hundreds of billable hours.

For example, consider substantive testing on accounts payable for one of the 75 annual audits. An associate exports a transaction list from the client’s NetSuite instance into Excel. They spend an hour filtering and sorting to select a random sample of 60 invoices. For each one, they must locate the corresponding purchase order and receiving report in a SharePoint folder, open all three documents, and manually verify that the amounts, dates, and vendor details match. This three-way match process takes 8-10 hours per audit and is repeated for every client.

The structural problem is that audit management platforms are not data execution engines. They are designed to store evidence, not to connect to disparate data sources and run analyses. Using Excel macros or scripts is a common workaround, but these are brittle. A script written for one client's data export breaks when the next client has a slightly different column format, forcing the auditor back to manual work. This approach lacks auditable logs, robust error handling, and cannot scale across the firm's client base.

The engagement starts with mapping your firm's specific audit methodology. We identify the 3-5 most time-consuming compliance checks, such as revenue recognition testing or inventory counts, to define the initial scope. You receive a technical plan detailing the data sources, the specific tests to be automated, and the expected outputs before any code is written.

The core of the system would be a Python service using the Claude API for intelligent document analysis and pandas for data manipulation. Deployed on AWS Lambda, this service can securely process thousands of documents or transactions in parallel. For instance, it could connect to a client's SharePoint via the Microsoft Graph API, ingest a sample of 1,000 invoices, and perform a three-way match against purchase orders in under 5 minutes. All operations and results are logged in a Supabase (PostgreSQL) database, creating a complete, auditable trail of every test performed.

The delivered system is a simple web interface accessible only to your auditors. They can select a client, choose a compliance test, and upload the necessary data exports or point the system to a document folder. The system returns a clear report detailing passes, failures, and specific exceptions within minutes. This report can be exported and attached directly into your existing AuditBoard or Workiva workpapers, augmenting your primary platform with powerful, automated testing capabilities.