New Zealand

Data Analytics 

Whenever an extensive, detailed and thorough analysis of business data is required, KPMG’s Data Management Services team can extract the required data from your business applications, upload them to our own data analysis software, and perform the analysis based on your requirements.

Contact us

Philip Whitmore

Philip Whitmore

Partner, IT Advisory

+64 9 367 5931

Data is of significant value for the companies which use it as a part of their key business processes. High-quality data represents one of several critical factors that influence correct decision making, effective functioning of business processes and the ability to maintain a long-term competitive advantage.


Moreover, reliable and auditable data for the purposes of internal statistics or external reporting is essential in ensuring compliance with regulatory requirements.


Our services


  • Proactive identification of fraud, waste or abuse through the use of our K-Trace forensic data analysis methodology and tools.


  • Financial and data modelling to assess and enhance the quality and reliability of financial and data models, thereby helping to improve the overall quality of decision-making and the likelihood of a successful outcome.


  • Spend analysis to help you better understand your procurement and payment patterns, in order to identify opportunities for process improvement and efficiency gain.


  • GST transactional analysis to help ensure you are meeting your tax obligations, identify cash flow opportunities, recover GST overpayments, and be in a better position for an audit.


  • Data migration planning and assistance to help you maintain the integrity of your data as you move it from legacy systems.


  • Revenue leakage analysis to identify lost revenue and help improve margins.


The number of opportunities where you can use our Data Management Services is only limited by your requirements and imagination.




  • Providing insights that can allow you to make effective and timely decisions.
  • Predict and detect suspicious transactions, patterns, and relationships in your data before it becomes a problem.
  • Financial efficiency gains in income and expenditure related business processes.
  • Efficiently test whole populations of data, rather than just small samples.
  • More efficiently and effectively satisfy regulatory and compliance requirements.