by Bruce Carpenter, Vice President, Corporate Audit, SAP

Picture1In my last blog of this series, I discussed the value of data analytics to help organizations provide greater assurance over data integrity. I used the example of an insurance company, which was able to use data analytics to more accurately identify potential fraud prior to claim payment.

But just consider the data sources here. For this analysis to be accurate, it will involve more than just financial records. The age, location, gender, income level, and socio-economic background are just some of the additional factors that, together, can allow more accurate identification of potential fraud in insurance claims.

Much Big Data is generated externally to the organization. A good example is the publishing by Transparency International of a global corruption index that is updated annually. This ranks countries according to perceived levels of corruption, and can be used by companies to identify risks of, say, relocating shared services centers.

This Big Data is becoming increasingly important to the auditor in expanding a company’s risk horizons and requiring consideration of broader non-financial data. Another example is geo-social footprint data, created by the combined pieces of location information that a user divulges through social media, which ultimately forms the user’s location footprint.

Big Data concepts aren’t new. But now we have technology advances that allow us to access, analyze, and report data relationships that were previously not possible. These analytics can be used to create competitive advantage. But equally important are the technology choices made to ensure a cohesive fit with data output and analysis requirements.

So, the questions for the auditor are:

  • To what extent are you incorporating non-financial data in your assessment of organizational risk?
  • What sources of non-financial information are available to you, and might be useful to better understand aspects of organizational risk? (Be mindful of privacy requirements here.)
  • How can you increase your profile as a trusted advisor by making more effective use of these types of data?
  • What technology do you need to enable this transformation?

Let me know.

For more on this subject, read the other blogs in this series: Auditing on an iPad, Really?, Auditing on an iPad: Databases, Auditing on an iPad: The Bell Tolls for Audit Sampling.


This blog was originally published on The Decision Factor and has been republished with permission.