Data analytics: Data in motion tends to stay in motion

  • Forensic Data Analytics
  • Investigations, Litigation and Forensics
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John Kim

John Kim

Data analytics: Data in motion tends to stay in motion 

John Kim, Director - Control Risks and Matt Reeder, Associate - Orrick Herrington & Sutcliffe LLP

This is the second article in a two-part series. 

In the first part of our series, “Developing a data analytics–enabled compliance program for the real world,”[1] we offered a three-step method for building data analytics–enabled compliance systems incrementally upon existing data sets and capabilities. Now, we turn our attention to how data analytics can enhance compliance programs that have inventoried their current capabilities, identified useful data sets, and mobilized their resources to execute an established plan. 

The hallmarks of an effective data analytics–enabled compliance program are adaptability and specificity. The more adaptable a data analytics program is, the more readily it can integrate new data sources, respond to new regulatory or legal requirements, and be applied across changing business practices. Taking a multitiered approach to data analytics and implementing a continuous feedback loop will ensure an appropriate level of adaptability. Data analytics outputs must be sufficiently specific. This specificity ensures that effectiveness is measurable. Vague evaluation criteria or outputs based on loose correlations do not yield actionable information.


Copyright 2020 CEP Magazine, a publication of the Society of Corporate Compliance and Ethics (SCCE)

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