MIT Sloan | Mr. NFL Team Analyst
GMAT 720, GPA 3.8
London Business School | Mr. Consulting To IB
GMAT 700, GPA 2.4
Kellogg | Mr. Big Beer
GMAT Waived, GPA 4.0
Harvard | Ms. Indian Quant
GMAT 750, GPA 7.54/10
Darden | Mr. Corporate Dev
GMAT Waived, GPA 3.8
Duke Fuqua | Mr. CPA To Finance
GMAT 700, GPA 3.5
Wharton | Mr. Big 4
GMAT 770, GPA 8/10
Wharton | Ms. General Motors
GRE 330, GPA 3.2
Stanford GSB | Mr. Venture Lawyer
GRE 330, GPA 3.4
Wharton | Ms. Project Mananger
GMAT 770, GPA 3.86
Stanford GSB | Ms. Digital Health
GMAT 720, GPA 3.48
Yale | Mr. Philanthropy Chair
GMAT Awaiting Scores (expect 700-720), GPA 3.3
Stanford GSB | Mr. MBA Class of 2023
GMAT 725, GPA 3.5
Foster School of Business | Mr. Construction Engineer
GMAT 710, GPA 2.77
Ross | Mr. Stockbroker
GMAT 700, GPA 3.1
Harvard | Mr. Harvard Hopeful
GMAT 740, GPA 3.8
Stanford GSB | Mr. LGBTQ
GMAT 740, GPA 3.58
Kellogg | Mr. Risky Business
GMAT 780, GPA 3.5
Kellogg | Mr. CPA To MBA
GMAT Waived, GPA 3.2
UCLA Anderson | Mr. Southern California
GMAT 710, GPA 3.58
Harvard | Ms. World Explorer
GMAT 710 (aiming for 750), GPA 4.33/5
Ross | Mr. Brazilian Sales Guy
GRE 326, GPA 77/100 (USA Avg. 3.0)
Kellogg | Ms. MBA For Social Impact
GMAT 720, GPA 3.9
Berkeley Haas | Mx. CPG Marketer
GMAT 750, GPA 3.95
NYU Stern | Mr. Washed-Up Athlete
GRE 325, GPA 3.4
Kellogg | Mr. White Finance
GMAT Not Taken, GPA 3.97
Stanford GSB | Ms. Russland Native
GMAT 700, GPA 3.5

Nekrasz Teaches Students That Looks Can Be Deceiving

Frank Nekrasz, Jr., a tattooed iMSA professor wearing a biker vest.Frank Nekrasz, Jr. jokingly refers to himself as a “walking disruption.” He’s traded in the clean-cut, suit-and-tie look for a long goatee, sleeveless shirt, and biker vest that reveals multiple tattoos on each arm. He doesn’t look like anything you’d expect from an accountant. He admits he used to turn quite a few heads when he’d walk to the front of the room on the first day of class – but now he says his students in Fraud Examination (ACCY 518) have come to expect the unexpected.

“There are no surprises anymore. Everyone just knows me as Dr. Frank, and they know I don’t look like all their other professors,” said Nekrasz, who is also teaching a four-week course in the iMSA program for the first time this year – exposing his unique look to a whole new set of students unfamiliar with the eccentricity.

But that unique persona makes Nekrasz, who is also a certified fraud examiner, good at his job. He’s different. And he trains his students to think differently. He teaches them to challenge assumptions, which can be a valuable quality to have when you’re sniffing out crime.

“I teach the dark side,” he said. “As a fraud guy, my perspective is that most people are bad unless they can show me they’re not. Being cynical makes you aware and alert and ultimately more prepared to catch criminals.”

Nekrasz admits crime hasn’t changed all that much over the years. Employees are still stealing from their company. Management makes promises they can’t keep, and then they try to “cook the books” toward the end of a fiscal period to cover their tracks. What has changed are the tools forensic accountants use to catch the bad guys. Disruptive forces like big data and artificial intelligence allow fraud examiners to analyze full data sets instead of just sampling certain transactions, as they’ve done for many decades. According to the Association for Certified Fraud Examiners (ACFE), 64% of organizations say the increased volume of transactions they can review with data analytics will be very beneficial to their anti-fraud programs.

Nekrasz knows that, soon, sophisticated criminals will adjust back, developing techniques to outsmart these big data and AI tools. The ACFE reported that occupational fraud cost businesses more than $7 billion in 2018 alone – and it could get much worse. Looking into his crystal ball, Nekrasz sees a future where human oversight to these technological advancements will be more critical than ever.

“Even in big data analysis, human expertise is so important. At first glance, the raw data may look okay, but the trained human eye can see irregularities that even machines cannot,” said Nekrasz, who is developing a case study for his iMSA course that uses the data analysis technique, Benford’s Law.  “What I do in the case is I show students that while big data is a powerful tool if you don’t truly understand what you’re analyzing, you can be fooled by the data.”

This outside-the-box thinking makes Nekrasz a great teacher, and it helps develop great students. So don’t ask Dr. Frank to conform to industry standards. That’s not him. And “industry standard” isn’t the benchmark for students at Gies College of Business. Just like Frank Nekrasz, Jr., we are disruptive. We are forward-thinking, and we are committed to developing the next generation of business leaders.

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