By Christopher M. Ferguson
Faced with shrinking budgets and resources, for more than a decade the IRS has been forced to do more with less. It has responded by turning to big data analytics. In recent years, the IRS has amassed massive amounts of taxpayer data and developed sophisticated proprietary systems for analyzing this data in order to modernize its operations. By the IRS’s account, these efforts will yield huge dividends, permitting it to identify and focus enforcement resources on the truly noncompliant, creating greater accuracy and fairness in the audit selection process and more effective criminal enforcement. The IRS believes that big data analytics will be a key tool in its arsenal as it works to shrink the $440 billion (or larger, by many estimates) tax gap.
What is Big Data?
As the name implies, “big data” refers to data sets that are too large or complex to analyze using traditional methods. Big data is typically defined by three features: 1) volume (the sheer size of the data); 2) velocity (the speed at which it is generated); and 3) variety (the various media and formats that data assumes).
What has brought the phrase “big data” into the public vernacular over the last several years are advances in technology that enable human institutions (corporations, government agencies) to manipulate and utilize big data. Sophisticated algorithms and artificial intelligence (AI) systems are able to ingest massive amounts of data from diverse sources and use it to identify patterns or predict behaviors and outcomes in ways that were recently unimaginable. Companies use big data to personalize advertising. Political campaigns use it to microtarget voters. Healthcare providers use it to improve patient outcomes. And the IRS has entered the game in a major way, harnessing big data to better predict and identify tax noncompliance as well as more effectively prosecute willful noncompliance.
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