AI-Powered Custom Analyses for Auditors

With AUDAVIS AI, client data can be analyzed, prepared, reconciled and visualized dynamically in natural language and transferred into individual dashboards. This is a powerful tool for auditors as well as for tax auditors and internal auditors when auditing corporate financial data.

AI in financial auditing and tax auditing: combining standardized audit procedures and flexible analyses in a meaningful way

Artificial intelligence will change financial auditing and internal auditing. However, it is not a miracle cure that can assess client data fully autonomously or replace audit decisions. In the financial statement audit in particular, traceability, methodological certainty, documentation and professional reliability remain essential.

The decisive question is therefore not whether AI is used, but how it is used.

Standardization as the basis for audit-proof analyses

For standard analytical audit procedures, AUDAVIS deliberately relies on predefined data models and structured audit pipelines. These include, for example, data reconciliations, expectation analyses and journal entry testing.

The advantage of this approach is obvious: recurring audit procedures can be performed efficiently, consistently and traceably. The underlying data models create clear structures, reduce manual effort and support audit-proof execution.

You could say that for many standard audit procedures, AUDAVIS already provides auditors with well-developed, reliable "roads".

When the audit requires individual paths

In practice, however, questions repeatedly arise that are not fully covered by predefined standard pipelines. Client structures differ, data formats vary, and individual audit procedures require custom analyses or additional evaluations.

This is exactly where generative AI unfolds its added value for the auditor in AUDAVIS.

With AUDAVIS AI, auditors can analyze, prepare, reconcile and visualize data dynamically and in natural language. Individual dashboards can also be created flexibly in this way. AI thus complements the standardized audit processes where special questions require a specific analysis.

The right use of AI: controlled, traceable and close to the audit

The added value does not lie in letting AI "decide" about client data in an uncontrolled manner. Rather, it is about providing targeted support to auditors: when exploring data, developing custom analyses, visualizing anomalies and preparing audit-relevant information in a structured way.

AUDAVIS is continuously expanding the number of standardized audit procedures. At the same time, auditors remain flexible when custom analyses are required. Standardized data models and generative AI are not opposites but complement each other.

The future of digital auditing therefore does not lie in fully automating audit judgments, but in the intelligent combination of proven standard processes and flexible, AI-supported analysis.

Learn more at www.audavis.ai

AUDAVIS – the AI platform for financial statement audits. Automated working papers, risk analyses and intelligent data analytics for auditors.

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