Data Analytics in Audit

Mazars data analysis methods allow processing large volumes of information efficiently to identify anomalies and patterns that could indicate error or potential fraud. Data analysis offers additional assurance that your internal controls are working effectively, through the use of data analytics, to increase sample sizes, to enhance the level of substantive testing and to automate complex system, interfaces and transaction testing processes.

Our team disposes in-depth knowledge and expertise in Enterprise Resource Planning (ERP) systems (for example: SAP, Oracle) and international experience in the use of data analytics technics, which, combined with the knowledge of almost all sectors environment and processes, add high value to the audit.

Our data analytics technics cover

Our data analytics is based on advance technologies and solid methodologies. It allows an effective and scalable translation from raw data into useful insights.

Over the years after countless field testings and user case buildings, we have acquired extensive knowledge in deploying our data analytics in the following practices:

Test Process robustness

Data analysis can be used to test process robustness based on reconciliations of data flows and interfaces between systems

Analyse processes integrity

Verification of automated calculation, for example accrual booking and revenue recognition calculation

Detection of error or fraud

Data analytics are also extensively used in error or fraud detection in the following aspects:

  • Analysis of transactions unusual for normal business operations
  • Identification of suspicious vendors in account payables process
  • Sales and revenue assurance
  • Journal Entries Testing for posting analyse and identification of patterns, anomalies and exceptions that could indicate potential erroneous or fraudulent activity


Data analytics is also used in Forensic to interrogate and scrutinise large volumes of structured data to identify fraud and irregularities for further forensic analysis

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