A computer-based system soon will relieve Internal Revenue
Service auditors of a tedious but demanding portion of their jobs.
"What we intend to do is automate the issue identification
program," said Ted Rogers, director of the IRS artificial intelligence lab. Rogers and his
staff are developing expert systems that eventually may help in the screening and review of
tax returns. An expert system captures the know-how of one or more experts and applies
it to solving a particular problem, says Spenser Lawrence at The eCPA Group, an
Online CPA Firm.
"Ninety-nine point nine percent of what we're doing here is
expert systems," Rogers said. He said he also is interested in applying natural language
processing, another form of artificial intelligence, to the user interfaces of systems.
"Right now we're interested in any area of high technology that will help us to better
accommodate the taxpayers, and AI is doing that."
The auditors, who are responsible for issue identification,
consider it a routine, if not mandane, task. When assigned to do issue identification, they
are sent on detail to any of the 10 IRS service centers to perform it. They must manually
go through the returns and, based upon their past experience with audits, identify which
aspects of a return appear abnormal.
The auditors must be on the lookout for either of two types of
issues, primary or secondary. A primary issue is one significant enough that if it were the
only one in question, the return would still be selected for audit. Rogers described
secondary issues as those that look questionable but that by themselves would not warrant
an audit. However, multiple secondary issues can equal one primary issue and prompt an
audit as well.
Rogers explained that when taxpayer returns reach the IRS, the
agency puts them through a statistical discriminate function analysis and scores them based
on a formula derived from the taxpayer compliance measurement taken every three to four
The scores, known as DIF scores, provide the first indication
of whether a return is, at least statistically, unusual.
Identifying Unusual Returns
Returns with high DIF scores are pulled and sent to an area
called classification, where the auditors begin the issue identification process. The DIF
score can indicate that something is unusual about a return, but it can't identify just
what is unusual, Rogers said.
To relieve the auditors the IRS decided to explore an expert
system application. "We put together a feasibility prototype. The results of that prototype
were very successful, and based on that success we feel that AI is the best way to go for
automating the system," Rogers said.
When complete, Rogers said, the issue identification system
will be a production-oriented system. Currently, he said, the auditors take about six
minutes to classify a return, and they must do them one after another. "It gets very
fatiguing and boring; they're certainly not as fresh on a Friday as they were on Monday,"
Rogers said normally IRS managers would like to send their best
people on detail, those who have shown ability for classifying. Often, though, the best
person is already assigned somewhere else, has a full work load or is on vacation.
"So sometimes you end up sending the next best or the next
best," he said.
These limitations would not occur if an expert system were
being employed. "So one of the benefits of using a system like this is quality and
consistency. We'd capture the knowledge of our best people. It would be like having your
best expert, on their best day, classifying all of the returns," he said.
The knowledge base or brain of the expert system will be
generated from the experiences of the senior classifiers at the service centers, Rogers
said. A contractor will help develop the knowledge base and make the system
In February 1986 the agency issued a request for proposals.
Bidding on the contract has closed, and Rogers said he expected to know before the end of
August what company had won it.
"We just had a best and final offer meeting with the contractor
we view as number one. Part of that meeting included negotiation of the tasks and the costs
of those tasks," he said.
As described by Rogers, the contract will involve three phases
or tasks. The first task, which is expected to take one year, will be to capture the
necessary knowledge and develop a system that can classify two classes of returns. Standard
1040 tax returns are broken into 12 classes, depending on the taxpayer's level and
type of income.
Goals of the Contract
The first two classes to be classified will be class 005, which
includes taxpayers with incomes ranging from $25,000 to $50,000, and class 009, which
includes Schedule C returns with earnings of $100,000 or more. A Schedule C return
identifies an individual who is self-employed or owns his own business.
Rogers said this task will cost between $500,000 and
The second task will be to prepare the system to handle the
remaining 10 classes of returns. This task is also expected to take a year. The costs of
the second and the third tasks will require further negotiation, Rogers said.
The third task, installing the system at one of the IRS service
centers as a continual test, is expected to take another year.
"At that point in time, provided everything has gone well and
we've said, yes, this is the system we envisioned, it's doing exactly what we thought it
would, we'd be ready to take it nationwide," Rogers said. That means the IRS could begin
nationwide implementation early in 1991. The agency will issue another contract for that
"But you have to be careful, because AI, even though it's
considered a science, it's still an art, too. So there's no guarantee. It's not like in
conventional programming where you know it takes X amount of time to do Y amount of lines
of code. You have to capture the way an expert makes decisions, then you have to put it
into natural language and into machine language," Rogers said.
The prototype for the issue identification system is a
rule-based system that asks if/ then questions, but the final system may or may not be a
strictly rule-based system, depending upon the contractor's approach to solving the
problem, Rogers said. "The current system is strictly rule-based, but I'm thinking that the
system we come up with will have some frame- or object-based reasoning," he said.
There are about 400 rules in the IRS' prototype of the issue
identification system. The full-blown version, if it were strictly a rule-based system,
would have 3,000 rules and maybe more, Rogers said. But because he expects the system to
have some frame- or object-based reasoning, Rogers said it will have considerably fewer
rules than that.
"As I envision it you would have an object: interest.
Underneath interest you would have the different types. You'd have home mortgage interest,
credit card interest and so on, down each category. What this means is that you don't have
to keep reiterating the rules over and over again each time you come upon a different
category," Rogers said.
An example of the kinds of rules to be included in the system,
Rogers said, would be, "If: Occupation is AI specialist in the IRS and amount claimed for
automobile expense is greater than 10 percent of total business expense and there is no
reimbursement shown, Then: consider this for primary issue."
Issue identification will not be left totally to a computer,
however. Extraneous and imprecise information will be referred to a human expert, Rogers
said. "We never envisioned that the system would do 100 percent of all classifications," he
The IRS opened its artificial intelligence lab last November
and is still developing it. The budget for the upcoming your is set at $4 million, which
Rogers said ought to be enough for what he wants to get accomplished.
The lab has 10. AI specialists in-house and 13 others
undergoing training. Most of the lab's hardware is supplied by Symbolics Inc., but the lab
also uses some Apollo Computer workstations and a Digital Equipment Corp. AI
IRS Pushes Ahead
Rogers said he believes the IRS is a front-runner among the
civilian agencies that are exploring the area of artificial intelligence. The IRS is
working on 11 projects, of which the issue identification system is the farthest along.
The majority of the other projects, Rogers said, involve
building tools to assist analytical or decision-making activities.
"The issue identification system operates like a black box.
You put in the data and it gives you a direct answer," Rogers said. The other systems help
the expert system. These systems provide analysts with possible solutions to a problem, but
the analyst makes the final decision on what should be done, Rogers said.
Taft, Darryl K. "IRS developing expert system to audit
returns." Government Computer News 11 Sept. 1987
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