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Data analytics: Data in motion tends to stay in motion

Matt Reeder (mtreeder@orrick.com) is an Associate with Orrick Herrington & Sutcliffe LLP in Washington, DC. John Kim (john.kim@controlrisks.com) is a Director with Control Risks in Washington, DC.

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.

With these hallmarks in mind, we describe three data analytics techniques that will empower a mature, data-enabled compliance program to apply data analytics more effectively. They are rules-based tests, statistical and trend analyses, and machine learning. Understanding these techniques will allow compliance professionals to work toward incrementally adopting a multitiered approach to data analytics.

Each of these techniques has unique costs and benefits, but they can work together. Adopting all three maximizes detection rates, minimizes false positives, and marshals more useable data in service of the compliance function. Furthermore, applying all three techniques creates a virtuous feedback loop that fosters adaptability. This full-fledged application of data analytics creates momentum for the compliance function that augments, amplifies, and multiplies the effects of the more traditional components of a compliance program.

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