Article Review 2
I n 1972, psychologist Daniel Kahneman, who was awarded the Nobel Prize in Economics 30 years later, and his associate, Amos Tversky, coined the term “cognitive bias,” which refers to the tendency of individuals to make systematic judgment errors when
making decisions. These errors typically result from information- processing shortcuts or heuristic behaviors that are “hardwired” or embedded into human decision-making processes.
Dozens of cognitive biases have been identified and catalogued by psychologists, including several that are often mentioned in everyday conversations. “Gambler’s fallacy,” for example, refers to the belief that the likelihood of a future event is impacted by
random and unrelated past events. It is common to find a casino patron keeping a written record of the outcomes of a roulette wheel, ostensibly to use that information when placing future bets; however, each spin of a properly balanced roulette wheel pro- duces an outcome that is unrelated to that of past and future spins.
Exhibit 1 lists several other widely recognized cognitive bias- es that have a persistent—and typically adverse—impact on the quality of everyday decisions. Keen advertising specialists and political campaign directors rely on the “bandwagon effect” or “herd instinct” to trigger behavior among consumers and voters. Regulatory and law enforcement authorities are routinely exas-
Cognitive Biases in Audit Engagements
A C C O U N T I N G & A U D I T I N G a u d i t i n g
JUNE 2012 / THE CPA JOURNAL40
By Michael C. Knapp and Carol A. Knapp
Errors in Judgment and Strategies for Prevention
perated by the “ostrich effect” that causes certain individuals to discount public health alerts, ignore hurricane evacuation warn- ings, and refuse to read the caveats and dis- claimers affixed to food and other con- sumer products. In our judicial system, jurors might fall prey to the “guilt by asso- ciation” fallacy and thereby ruin the life of an unlucky but law-abiding citizen who happened to be in the wrong place at the wrong time.
Cognitive biases can cause errors in judgment across practically every context in which humans make decisions, but espe- cially so in complex and pressure-packed settings, such as when auditors conduct independent audits. Psychological studies have shown repeatedly that cognitive bias- es often influence auditors’ decisions. There are isolated cases in which overt eco- nomic self-interests have allegedly influ- enced or biased auditors’ judgments. An excessive desire to please a client does not qualify as a cognitive bias, however; it is, instead, often a symptom of impaired auditor independence.
The following discussion provides an overview of the general ways that cogni- tive biases can impact independent audi- tors and identifies the specific cognitive biases that seem most likely to induce sys- tematic judgment errors during audit engagements. It also introduces several techniques that have been developed to “de-bias” human judgments across a wide range of decision-making contexts, includ- ing auditing.
Cognitive Biases in an Auditing Context Cognitive biases affect independent audi-
tors in multiple ways. First, auditors have a principal responsibility to evaluate a wide range of decisions made by other parties— decisions almost certainly impacted by cog- nitive biases.
Second, auditors must be concerned with how cognitive biases affect the multiple tiers of decisions made throughout the audit process. Staff accountants, audit seniors, audit managers, audit engagement partners, and concurring or review audit partners all have an opportunity to inject their own cog- nitive biases into the numerous decisions made during every audit engagement. In fact, the individuals who make the judg- ments most relevant to auditors—namely, client executives and accountants—might
be aware of the types of cognitive biases that influence auditors’ judgments. Those individuals could use that knowledge to elicit those biases, thereby manipulating auditors’ decision-making processes.
Lastly, cognitive biases can also influence the decision-making processes of third par- ties who pass judgment on the quality of an auditor’s performance. Those parties include peer reviewers, regulatory authorities, dis- gruntled investors, and, occasionally, jurors. Exhibit 2 presents brief descriptions of the cognitive biases that seem most likely to influence auditor decisions.
Confirmation bias. When investigating a management assertion that underlies an account balance or other financial state- ment item, auditors establish a mental hypothesis about whether that assertion is materially accurate. They typically begin their testing under the assumption that a given assertion is valid. This assumption might trigger confirmation bias on the part of auditors. Research demonstrates that decision makers tend to be predisposed to search for evidence that confirms rather than rejects their expectations. This bias often manifests itself through auditors’ will- ingness to accept management representa- tions that support a given assertion, while rejecting stronger types of evidence that suggest that it is invalid.
Even a cursory review of the Accounting and Auditing Enforcement Releases issued by the SEC reveals numerous instances in which auditors have apparently fallen victim to confirmation bias. For example, while auditing United States Surgical Corporation, a medical equipment manufacturer, one audit engagement team collected considerable evi- dence suggesting that the company was cap- italizing routine production expenses. Despite that evidence, the auditors chose to accept the repeated statements of middle- and top- level managers, claiming that the amounts being capitalized were not production expenses but, rather, “retooling” costs prop- erly chargeable to long-term asset accounts. The amounts being capitalized were, in fact, production expenses that management was deferring in order to enhance the company’s reported operating results.
Similarly, the auditors of Perry Drug Stores, a large drugstore chain, collected evidence—including the results of physi- cal inventory counts—indicating that the company’s year-end inventory balance was
materially overstated. When executives insisted that the physical inventory data could not possibly be correct and agreed to do a thorough recount after the audit’s completion, the auditors signed off on the inventory value. The subsequent recount confirmed that the year-end inventory value had been materially overstated.
Availability bias. Kahneman and Tversky found that decision makers tend to predict the likelihood of a given event based upon how easily an example of that event can be brought to mind—that is, whether such an event is readily “avail- able” in one’s memory. This bias can dampen the professional skepticism that auditors should invoke during every audit engagement and can render them less like- ly to uncover a fraudulent scheme perpe- trated by a client. Because client fraud is such a rare event, most auditors do not have a vivid fraud “blueprint” stored in their memory. That is, auditors’ mental image of the typical audit client is an honest organization dedicated to prepar- ing materially accurate financial statements.
In the early 1980s, Crazy Eddie Inc., a consumer electronics retailer based in New York, was a darling of Wall Street, large- ly due to the company’s flamboyant founder, Eddie Antar. Unknown to the investing public, the company’s rapidly ris- ing revenues and profits largely resulted from a massive accounting fraud orches- trated by Antar. Because most auditors never encounter such a large-scale fraud during their careers, Crazy Eddie’s audi- tors most likely did not have a mental blueprint available in their memory for
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Bandwagon Effect
Gambler’s Fallacy (Monte Carlo Fallacy)
Guilt by Association Fallacy
Illusion of Control
Just-World Phenomenon
Ostrich Effect
Stereotyping
Sunk-Cost Fallacy
EXHIBIT 1 Well-Known Cognitive Biases
JUNE 2012 / THE CPA JOURNAL42
such a scam. Over the past several decades, accounting frauds involving major compa- nies have become more frequent, but are still relatively uncommon.
Familiarity bias. Many of the dozens of cognitive biases identified by psychological researchers are related or overlap; this is cer- tainly true of availability bias and familiari- ty bias. To simplify and expedite decisions for common and recurring decision-making scenarios, humans are prone to choosing familiar alternatives that have worked in sim- ilar cases in the past. For example, when updating a client’s permanent workpaper files, auditors typically find that there have been few, if any, year-to-year changes in the accounting policies and procedures relevant to most accounts. As a result, auditors might be lulled into a false sense of complacency that causes them to quickly apply the all-too- familiar “SALY” (same as last year) con- clusion when completing that task.
Familiarity bias may have caused the longtime auditors of Happiness Express
Inc., a toy manufacturer, to incorrectly decide that there had been no major changes in the way that the client processed its credit sales. In the past, nearly all of the company’s credit sales had been preap- proved by its finance company, a fact that was documented in the prior year’s audit workpapers; this was no longer the case, however, during the year in question. The change in the nature of most credit sales meant that the collection risk posed by the large amount of year-end accounts receivable was dramatically higher than in the previous year. Overlooking this risk factor almost certainly contributed to the auditor’s failure to discover that the net realizable value of the receivables was materially overstated.
Anchoring and adjustment bias. An auditor assigned to a given account implic- itly or explicitly establishes a mental “anchor” or expectation regarding that account’s true dollar value. As the auditor collects evidence regarding the material
accuracy of the valuation assertion for that account, she will adjust the expected balance either higher or lower. Psychological research demonstrates that adjustments made by a decision maker away from an initial anchor tend to be insufficient. That is, decision makers tend to fixate on their initial estimate or expec- tation as they progress through the evi- dence-collection process.
Auditors appear to be prone to the anchoring and adjustment bias, particular- ly when auditing accounting estimates, such as valuations for accounts receiv- able, inventory, and loan portfolios. In such cases, auditors tend to anchor on the com- pany’s preaudit estimate for those accounts. For example, the SEC criticized the audi- tors of Just for Feet Inc., an athletic shoe retailer, for failing to persuade the client to significantly increase its allowance for inventory obsolescence in the face of audit evidence that suggested the allowance was understated. The auditors proposed an audit adjustment to increase the allowance account but eventually relented and decided to accept the preaudit account bal- ance, which the client maintained was reasonable. In fact, the company had inten- tionally and materially understated the allowance account.
Uncertainty aversion. Significant uncertainty in a decision-making scenario causes most individuals to feel uncom- fortable, if not downright “stressed out.” Choosing a decision alternative that does not have a precise or clear-cut out- come can extend or amplify that stress. To eliminate the stress posed by uncer- tainty, humans are prone to making deci- sions too quickly and to choosing deci- sion alternatives that have clear-cut out- comes. Not surprisingly, such hasty, “end it now” types of decisions often prove to be bad ones.
An example of uncertainty aversion can be found in the ESM Government Securities Inc. fraud, a rare instance in which the audit engagement partner was an active participant in the client’s account- ing subterfuge; this complicity resulted in a substantial prison term for that partner. The fraudulent scheme revolved around a series of complex financial derivatives transactions that the company was using to grossly distort (i.e., improve) its reported financial condition. When the concurring
Confirmation Bias: The tendency to search for and favor evidence that confirms one’s beliefs, research hypotheses, or other expectations.
Availability Bias: A phenomenon that causes decision makers to estimate or fore- cast the likelihood of an event based upon how readily they can recall an example or instance of that event.
Familiarity Bias: The tendency to choose the same decision alternative in a new deci- sion-making context that is identical or similar to a decision context faced in the past.
Anchoring and Adjustment Bias: Applies to situations in which an individual must arrive at a numerical estimate by starting from an initial value that is subsequently adjusted to arrive at the final estimated value. In such cases, the adjustments made from the initial “anchor” tend to be insufficient.
Uncertainty Aversion: The tendency for decision makers to be averse to circum- stances and decision alternatives involving uncertainty.
Framing Bias: The format used to present information relevant to a decision might influence the decision alternative subsequently chosen.
Halo Bias: The tendency for one observed or known trait of a person or object to positively (or negatively) influence an individual’s perception of other traits of that person or object.
Irrational Escalation: A decision maker’s inclination to make irrational decisions to justify rational decisions made in the past.
False Consensus Bias: The tendency for decision makers to overestimate the degree to which other individuals agree with them.
EXHIBIT 2 Cognitive Biases Likely to Affect Auditors’ Decisions
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partner for the engagement reviewed those transactions, he found them extremely difficult to understand. At some point, the frustrated concurring partner approached the audit engagement partner and said, “I don’t understand this … so please tell me it’s okay and I will sign it.” Of course, the audit engagement partner maintained that the given transactions had been record- ed properly, and the concurring partner signed off on the transactions. Although this decision eliminated the stress-inducing uncertainty that the concurring partner was facing, it ultimately had traumatic conse- quences for him and his firm years later.
Framing bias. Often, questions will be framed in order to elicit responses that fur- ther the agenda of the questioner. One stereotypical example is that of a prose- cuting attorney facing a defendant accused of beating his wife; rather than asking the defendant whether he does so, the attorney frames the question, “So, Mr. Defendant, when did you stop beating your wife?” Framing effects are typical in political cam- paigns as well. Survey researchers realize that how a question is asked is often more important than the question itself. Unsuspecting citizens can be duped into providing responses that seemingly support a candidate or initiative that they oppose.
Because executives and employees gen- erally have a thorough understanding of the role and objectives of an independent audi- tor, they might frame evidence provided to auditors in a way that will elicit the audit outcome they prefer. Take the case of The North Face, a producer of outdoor apparel and sporting equipment. To enhance the company’s operating results as the end of its fiscal year approached, company executives arranged a series of fraudulent barter transactions with select- ed customers. Because the executives were familiar with their auditors’ materiality thresholds, they were able to structure the suspicious barter transactions in such a way that they induced the auditors to propose but then “pass” on an audit adjustment for them.
A more extreme case of a framing effect is the notorious fraud engineered by Barry Minkow, the founder of ZZZZ Best Company Inc. Minkow and his cocon- spirators created an entire accounting cycle of transactions to make it appear that ZZZZ Best was an operating entity when, in real-
ity, it was effectively a “hologram” of a corporation. Minkow’s elaborate hoax was intended to deceive multiple parties, includ- ing the company’s independent auditors.
Halo bias. There exists the tendency of decision makers to allow their assessment of one specific trait possessed by an indi- vidual to be influenced by that individu- al’s other traits. Research demonstrates that one’s judgment of the personal attractive- ness of an individual tends to influence the assessment of that individual’s intelligence.
For auditors, technical competence resides among the most salient personal characteristics of client executives. Because the stereotypical image of a corporate exec- utive is an individual who is technically competent, at least in one particular field, auditors tend to give those individuals the benefit of the doubt when it comes to assessing their other personal traits— including honesty. This bias means that auditors are inclined to accept management representations at face value.
Problem audits are replete with exam- ples of halo effects. Take the case of Golden Bear Golf Inc., a public company established by Jack Nicklaus. The media, investors, and other parties widely assumed that the company would be very success- ful because it involved the sport in which Nicklaus had been a dominant figure for decades. In fact, this halo effect was not deserved. In a few years’ time, the com- pany and its auditors were the targets of an SEC investigation. The federal agency found that two of Nicklaus’s subordinates had inflated the company’s unexpectedly modest revenues and profits by intention- ally misapplying the percentage-of-com- pletion accounting method. The SEC also concluded that Golden Bear’s auditors had relied too heavily on management’s oral representations during their audits of the company.
Related to the halo effect is the tenden- cy of auditors to overly rely on represen- tations made by a former colleague who has accepted a key management position with a client. Just because former col- leagues were scrupulously honest as audi- tors does not mean that their representa- tions should subsequently be accepted as indisputable audit evidence. In a case involving AMRE Inc., a home remodeling company, the SEC ruled that the compa- ny’s auditors had relied improperly on
“unverified representations” of a former colleague, based upon their “prior experi- ence with him and his reputation for integrity.”
Irrational escalation. Similar to other decision makers, auditors might fall victim to the tendency to dig in their heels and become entrenched in support of a deci- sion they made in the past, despite more recent evidence suggesting that the deci- sion was wrong. Irrational escalation is related to the anchoring and adjustment bias, as well as to the widely referenced “sunk-cost fallacy” that often prods investors to “throw good money after bad.”
The auditors of Ligand Pharmaceuticals Inc., a biotech company, faced the task of evaluating the sufficiency of a reserve for sales returns that the company had estab- lished for several new products. After ana- lyzing the reserve, the auditors concluded that the client had made a good faith effort to estimate the account’s period-ending bal- ance and that the balance seemed reason- able. Actual rates of return subsequently experienced by the company, however, suggested that the reserve was materially understated. Despite that evidence, the client and the auditors consistently reaf- firmed their commitment to the original projected return rates during the subsequent fiscal year. The audit firm was eventually sanctioned by the SEC for failing to encourage the client to increase the reserve once it became evident that it was almost certainly understated.
False consensus bias. Psychological research demonstrates that decision mak- ers tend to overestimate the degree to which others agree with them. This bias is often enhanced in an employment set- ting, where subordinates frequently engage in “impression management” tactics to ingratiate themselves with their superiors. Staff auditors, for example, might quickly agree with views expressed by their supe- riors to earn brownie points with them. The typically large disparity in the experience and expertise of the individuals assigned to an audit engagement team also predis- poses lower-level auditors to be reluctant to challenge their superiors’ decisions.
An audit manager who had served on the audit engagement team for Flight Transportation Corporation (FTC) was sanctioned by the SEC for failing to “stand his ground” when a controversy arose dur-
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ing an FTC audit regarding a revenue recognition issue. Initially, the audit man- ager concluded that the air charter compa- ny should not be allowed to record sever- al million dollars of suspicious revenue— revenue that was determined to be fraud- ulent following the release of the audit opinion. After discussing the matter with the audit engagement partner, however, the audit manager changed his mind and sup- ported the partner’s decision to approve the client’s recording of that revenue.
The audit manager later confessed to an SEC investigator that he never believed the given revenue should have been record- ed. He had agreed with the partner’s point of view because he realized the partner would render the final decision on the mat- ter and because he was concerned that if he questioned the partner’s position, his job might be jeopardized. Both the audit part- ner and audit manager were ultimately sus- pended from practicing before the SEC. The partner received a five-year suspen- sion, while the audit manager received a one-year suspension.
Additional Cognitive Biases Impacting Auditors
Several other cognitive biases identified by psychological researchers might also affect auditors’ decisions. Consider “dilu- tion bias,” for example. The quality of judg- ments made by decision makers tends to be diminished if there is considerable background noise in the decision-making context. That is, the presence of a signifi- cant amount of nondiagnostic information
tends to distract decision makers and dilute or lower the quality of their judgments.
In an auditing context, dilution bias is particularly problematic on initial engage- ments, when auditors must collect and pro- cess a wide range of information as they seek to obtain an adequate understanding of the client’s operations, accounting sys- tem, and internal controls. Some of the information that auditors collect will be only marginally relevant to this goal. This overload of information—or excessive background noise—tends to undercut the quality of initial audits. Corporate execu- tives who have something to hide can take advantage of the learning curve effect implicit in initial audit engagements by frequently changing auditors.
In 2010, the chief executive officer and chief operating officer of DHB Industries, a national producer of bullet-resistant vests, were convicted of intentionally misrepre- senting their company’s financial statements. DHB’s embellished operating results had allowed the two officers to reap nearly $200 million in illicit stock market gains. A key feature of the officers’ effort to conceal the fraudulent scheme was frequent changes in DHB’s independent auditors. Between 2000 and 2005, the company retained four different accounting firms to audit its annu- al financial statements.
In many decision-making contexts, mul- tiple cognitive biases can influence the judgments of decision makers. In the case of United States Surgical, the auditors’ judgments appear to have been impacted by confirmation bias, as suggested earlier.
Those judgments may also have been influ- enced by a “recency effect”; among the most studied cognitive biases are such “serial position effects.” Researchers have repeatedly found that the order in which decision makers collect items of evidence influences the weights that they ascribe to them. In many decision-making contexts, the recency effect is prominent, meaning that the latest or most recently collected items of evidence have a disproportion- ately large influence on decision makers’ judgments.
In the case of United States Surgical, the company’s auditors initially uncovered evi- dence suggesting that the company was capitalizing routine production expenses. To offset that evidence, the company’s management team produced bogus docu- ments and other evidence suggesting that the items were capital expenditures. The auditors were eventually swayed by this more recent evidence and accepted the client’s accounting treatment for the ques- tionable items.
Finally, another heavily studied cogni- tive bias is “hindsight” or “outcome bias.” This bias prompts third parties to judge the quality of a decision by its ultimate out- come, rather than by the rigor of the deci- sion-making process that produced it. Hindsight bias often causes auditors to face a barrage of criticism from third parties who rush to judgment when an unqualified audit opinion is subsequently proven to have been the wrong opinion. This criti- cism typically involves unsubstantiated allegations that the given problems in the company’s financial statements should have been obvious to the auditors. The U.S. Foodservice scandal provides a prototypi- cal example of a rush to judgment triggered by hindsight bias. In that case, the SEC charged an audit partner and audit man- ager with professional misconduct. Years later, however, a federal judge ruled that the SEC’s charges against the two auditors were unfounded.
De-biasing Techniques Over the past four decades, cognitive
psychology has primarily focused on iden- tifying and documenting the nature of cog- nitive biases. A secondary objective has been the development and testing of de- biasing techniques. One broad approach for lessening the impact of cognitive biases on
■ Using structured decision aids to guide decision makers’ judgments and to facilitate the review of those judgments
■ Using a brief, nontechnical tutorial to illustrate the impact that cognitive biases can have in a specific decision-making context
■ Making a decision process more transparent by converting large tasks into a series of discrete, smaller tasks
■ Requiring decision makers to develop alternative explanations that are contrary to their a priori explanation for circumstances or events that impact decisions they must make
■ Ensuring that decision makers explicitly consider the impact that their decisions will have on relevant third parties
EXHIBIT 3 Examples of De-biasing Tactics
JUNE 2012 / THE CPA JOURNAL 45
human judgments is the application of a critical-thinking strategy. Critical thinking involves a conscious and iterative process of reflecting, evaluating, and challenging one’s own decisions and decision-making processes with the intent of improving each. If properly applied, this “thinking about thinking” strategy can help decision makers identify cognitive biases influenc- ing their decisions and then choose the spe- cific measures that should be useful in con- trolling or eliminating them.
Exhibit 3 presents examples of measures that have proven useful in mitigating cogni- tive biases across a wide array of decision- making contexts. A particularly effective de- biasing technique, and one that is already widely employed by audit firms, is the use of structured decision aids. Academic research suggests that such decision aids tend to lessen the impact of cognitive biases on human judgments. For example, the use of comprehensive audit checklists reduces the likelihood that important changes in a com- pany’s key operational policies and proce- dures will be overlooked by auditors who fall prey to familiarity bias, similar to the events of the Happiness Express case.
Brief tutorials demonstrating the impact of cognitive biases in a specific decision- making context have also proven effective in minimizing their impact on human judgments. Such tutorials are particularly effective in mitigating availability bias. Although inventory is a common target of fraudsters, most auditors have not encoun- tered fraudulent misstatements of that account. Consequently, a preaudit tutorial reminding auditors of the methods com- monly used by dishonest clients to inflate inventory would make them more conscious of the circumstances that might indicate intentional inventory misstatements. Such tutorials might have been helpful in the audits of Crazy Eddie, because a key fea- ture of that company’s accounting fraud was overstating period-ending inventory. Among the ruses used by Antar to inflate his com- pany’s inventory was instructing subordi- nates to move merchandise overnight between the inventory count sites scheduled to be observed by auditors and routinely including consigned merchandise in physi- cal inventory counts.
Uncovering cognitive biases within deci- sion-making processes is more difficult, how- ever, when the relevant tasks are multi-
faceted. Converting large tasks into a series of smaller, more discrete assignments enhances the transparency of the decision- making process and increases the likeli- hood of detecting cognitive biases within that process. In an auditing context, this goal is accomplished by developing a written audit program consisting of a large number of bite- sized audit procedures. Of course, this bias- mitigating feature of audit programs is under- cut if auditors fail to complete their assigned audit tasks.
In the Just for Feet debacle, management goaded the auditors into accepting a materially understated allowance for inven- tory obsolescence. The auditors’ failure to
properly complete the audit procedure for that account contributed to their poor deci- sion. For example, the auditors did not con- sider all of the classes of inventory that the company’s own accounting policies dic- tated should be considered in determining the year-end balance of the allowance for inventory obsolescence.
Academic research demonstrates that the quality of problem-solving decisions is enhanced when decision makers are required to identify multiple explanations for the source or cause of a given problem. This de-biasing technique can be particu- larly useful in minimizing confirmation bias. For example, requiring auditors to develop alternative explanations for an unexpected fluctuation in an account that is contrary to the explanation provided by the client should reduce the likelihood that confirmation bias will influence the final audit conclusion regarding that account.
In the case of United States Surgical, management provided a seemingly viable explanation for the evidence collected by auditors that suggested routine production expenses were being capitalized in prop- erty and equipment accounts. Before inves-
tigating that assertion, the auditors could have developed alternative explanations for the evidence they had collected. One of those explanations would likely have been that management was intentionally capitalizing production expenses. In inves- tigating that possibility, the auditors would almost certainly have recognized that most of the evidence they had collected was more consistent with this explanation than the explanation provided by management.
A final de-biasing technique that can be helpful in an auditing context is stressing to individual members of the audit engage- ment team the impact that their judgments will have on third parties, such as creditors and potential creditors. This strategy tends to heighten decision makers’ feelings of accountability, which, in turn, tends to make them more committed to alleviating the effect of cognitive biases on their decisions.
This final de-biasing technique can be par- ticularly useful in mitigating the impact of cognitive biases in high-risk audit engage- ments. In the DHB case, company man- agement routinely switched auditors to help conceal their ongoing fraudulent account- ing scheme. Because recurring auditor changes is a key red flag commonly asso- ciated with financial statement fraud, audi- tors in such circumstances should consider the enhanced threat posed by the audit client to the economic interests of the third parties who will rely on their audit opinion.
Practical Guidance Cognitive biases can impair the decision-
making processes of any auditor. Being aware of the many different biases that typ- ically impact auditors’ decision making is the first step in overcoming them. The de-biasing techniques discussed above can provide additional guidance for auditors who are striving to guard against cognitive biases during audit engagements. ❑
Michael C. Knapp, PhD, CPA, CMA, is the David Ross Boyd Professor and Glen McLaughlin Chair in Business Ethics at the Price College of Business at the University of Oklahoma, Norman, Okla. Carol A. Knapp, PhD, CPA, is the John Mertes, Jr., Presidential Professor and an assistant professor of accounting, also at the Price College of Business at the University of Oklahoma.
Cognitive biases can impair
the decision-making processes
of any auditor.
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