AI Comes to the Tax Code
AI
Comes to the Tax Code
Governments turn to
machine learning to boost revenue as taxpayers seek to reduce their bills
IRVINE, Calif.—Tax cheats, beware: The machines are watching.
Governments
are increasingly relying on machine learning and data analytics to analyze
troves of data as they seek to detect tax evasion, respond to taxpayers’
questions and make themselves more efficient.
In
Brazil, the customs agency’s system for detecting anomalies now prompts more
than 30% of inspections. Canada next month will launch Charlie the Chatbot, an
automated system that will respond to inquiries about tax filing.
The
Internal Revenue Service is designing machine-built graphs to plot the
relationships among participants in business deals, giving auditors a new tool
to analyze transactions and detect tax avoidance. The agency is using
artificial intelligence to study notes that agency employees take when fielding
questions from taxpayers and testing which combinations of formal notices and
contacts are most likely to get a taxpayer who owes money to send a check.
The IRS scours data from inside and outside the agency for its
compliance initiatives, such as a recent effort to identify thousands of
high-income individuals who didn’t file returns. The government is now sending
tax collectors to knock on their doors.
“How do
you think we found these people?” said IRS Commissioner Charles Rettig at a
conference on artificial intelligence and taxes this week at the University of
California, Irvine law school. “It wasn’t on filed returns. These are
non-filers. There is a heat map that says where there are concentrations of
these people. We have sufficient data on these people.”
The IRS
criminal investigations unit uses Palantir Technologies, the data-mining firm,
to identify potential fraud cases for further inquiry.
“If I get
a first name and a cellphone number, you’d be shocked how much information
Palantir can provide,” Mr. Rettig said.
Some of
the IRS’s most sophisticated efforts are still in their early stages, and the
budget-starved tax agency has long struggled to update some of its decades-old
technology. It is too soon to tell how much impact these initiatives will have
and how they will compete against companies and accounting firms employing
similar technology in the constant cat-and-mouse game between taxpayers and
enforcement officials.
U.S.
states are already using artificial intelligence to target resources and
increasing the return per hour they get from each auditor, said Debbie Pianko
of the data firm SAS Institute Inc., which contracts with governments.
Real
risks exist if algorithms for audit selection inadvertently discriminate
against taxpayers by race or location. And relying on technology can make an
already impersonal agency even more so, perhaps confusing taxpayers who may
struggle to understand why the government is coming after them and want to deal
directly with people at the IRS.
“The
tools are only going to be as good as the people employing them,” said Victor
Fleischer, a UCI law professor.
Meanwhile,
tax preparers and accounting firms are turning to the same tools to keep tax
bills as small as possible. The big four accounting firms all have specialists
trying to use artificial intelligence to guide the advice they give clients.
To the
extent that tax laws can be described as formulas, machine intelligence can
make it easier for companies to find the optimal tax strategies. But tax law is
often full of gray areas, legal interpretations and changing rules.
That
means the human role in tax administration and tax planning may change, but it
won’t vanish. The tax world’s future looks more like “Iron Man” than “The
Terminator,” said Daren Campbell, a partner at EY LLP.
“We’re
supplemented by the machines, so we can make better decisions,” he said.
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