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Data & Analytics / Introductory

From Data to Audit Insights

KPMG MADA Program Team

October 2026

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Summary

The case objective is to demonstrate how to use Power BI and supporting data to apply a data-driven audit approach, identify and investigate unusual financial trends, correct data-mapping issues, develop meaningful business insights, and document conclusions using reliable evidence.

Content

This case study is designed to enable students to apply a data-driven audit approach by using Microsoft’s Power BI and supporting data sources to identify and investigate unusual financial trends, correct account-mapping and classification issues, develop meaningful business insights, and prepare audit documentation supported by reliable evidence.
 
Through a structured multi-period case study of a multi-component entity, students serve as audit professionals transforming the audit into a modernized, data-driven approach. While these tasks could theoretically be initiated in Excel, the scale of multi-year, multi-component subledger data is designed for students to leverage relational data modeling and visualization in Power BI.
 
The learning objectives of this case study are as follows:

  1. Explain data strategy concepts including data lineage, granularity within data levels, and how to align data requests with audit objectives.
  2. Apply critical thinking to evaluate a multi-year consolidated trial balance, identifying outliers and unexpected variances before consulting client management.
  3. Execute relational data operations by identifying and linking Relevant Data Elements (RDEs) across disparate data sources (Trial Balances, Company Mapping, and Subledger Details).
  4. Modify structural mapping databases to correct data pipeline errors and dynamically update analytical dashboards.
  5. Formulate complex audit expectations combining qualitative risk factors (walkthroughs, board minutes, external market indices) with quantitative trends.
  6. Interpret subledger analytics to identify operational insights (e.g., product sales trends, customer attrition, product cannibalization) and communicate them as client value stories.