The amount of electronic data that corporations produce can be overwhelming and can result in substantial cost.
The amount of digital data that companies create and manage is growing exponentially. As a result, organizations face a variety of complex issues with digital data. Our professionals provide a full spectrum of services to help organizations better manage their data and the valuable information contained therein. We have vast experience helping clients with information life cycle management and enterprise data risk management and disposition challenges.
Where the need arises to preserve or otherwise handle data beyond the normal business function, we have a deep bench of global professionals to help with forensic data identification and collection in response to requests for information for litigation and investigations. We also help our clients to understand what is contained in their data through our Managed Review Services, our Forensic Technology Consulting, and our sophisticated Data Analytics capabilities, all of which can assist with detecting fraud and misconduct.
The volume of data and electronic information continues to grow at an astonishing rate. This growth is transforming all aspects of business and changing the way companies manage and extract value from data. As organizational complexity increases, the demand for advanced forensic data analysis rises. KPMG Forensic offers services to meet the challenges of constantly changing regulatory environments and industry or sector needs.
KPMG provides powerful data analyses that can create immediate value for our clients. We can identify opportunities to stop fraud, waste, and misappropriation of resources that have an immediate impact on the bottom line. We use graphic depictions and tabular results to identify trends and behaviors and to highlight high-risk categories. We also perform data analytics to identify unknown patterns that may be indicative of fraud, misconduct, waste, or abuse.
We assist clients with:
KPMG examines factors behind the low detection rate of fraud using analytics.