Fraud Fighter

The messages from Jimmy started simply, according to Massachusetts lawyer Cindy Tsai—a compliment, a shared joke, a late‑night conversation that stretched longer than she expected.

By the time Jimmy said he could teach her to invest in crypto like he did, she trusted him. She believed him. And when the trading platform he recommended showed her account balance climbing, the lawyer felt something she hadn’t felt in years: Hope.

But the profits were fake, the platform was controlled by criminals, and the man she thought she loved never existed. By the time she realized the truth, $2.5 million was gone.

Stories like this drive Krina Shah (MLDS ‘25) to build automation systems that can spot deception long before a victim ever sees the red flags.

Krina is a fraud engineer at Morgan Stanley, where she works with the fraud-detection squad focused on crypto scams. She joined the company in January. 

“I get to hear some very interesting fraud stories in the fraud space, especially romance fraud,” Krina said. “Who knew love could cause so much loss?

The scope of victimization in this arena is staggering.

FBI statistics from 2024—the latest full year for which data is available—show $9.3 billion in crypto-related fraud losses. That was a 66 percent increase in losses from 2023 and came from nearly 150,000 complaints, according to the FBI 2024 Internet Crime Report.

Investment scams similar to the one that hoodwinked the Massachusetts lawyer accounted for $5.8 billion in losses—more than all crypto-related fraud losses in 2023.

That reality has Krina diving deeply into her new field to arm herself for the battle ahead. 

Krina’s job centers on building automation algorithms to detect fraud and verify identities. In this, she is a fighter on a new frontier, part of an AI-driven arms race pitting highly sophisticated fraudsters against equally powerful gatekeepers—both sides wielding the same new and rapidly developing technology. 

“Working for such a big organization, I am particularly excited about how analytics and detection is done on such a large scale,” Krina said. “I love working in teams and brainstorming with people, and this job has allowed me to work with some of the best experts in the field.”

Krina landed at Morgan Stanley thanks to her time in Northwestern Engineering's Master of Science in Machine Learning and Data Science (MLDS) program. Prior to MLDS, she spent five years as a data scientist in digital-asset strategy and the economics side of finance.

Krina was drawn to the MLDS program because of its internship opportunities. As a student, she was a data science intern for SONIC Research Group—a Northwestern-based group that studies how social and knowledge networks form—and Calamos investment firm. 

Those experiences, along with the lessons she learned in the classroom, allowed Krina to seamlessly transition to Morgan Stanley, armed with practical experience that is proving vital.

As for the case of the Massachusetts lawyer, no one has been arrested to date. The victim joined a volunteer group that aims to expose and educate the world on the proliferation of these scams.

Krina, meanwhile, is carving out her own niche in the fraud-fighting arena, relying on the lessons learned in MLDS as she works to combat crypto scams.

“The subjects that MLDS offered are so relevant, and they also keep changing the curriculum based on how the industry and the job market moves,” she said. “These courses have really shaped my understanding on how data science, analytics, and scaling align with each other.”