Solving Big Business Problems

When CMU alumna Danamichele Brennen flipped through the pages of her daily college planner, she realized what a difference a day can make.

Danamichele is the CEO and co-founder of badbank.ai, a tool that uses artificial intelligence to transform messy financial data into actionable information. Before starting the company, she held leadership roles in the fintech, financial services, travel and genealogy industries.

She earned a master’s degree in public policy and management from CMU in 1989, and recently stumbled on the planner. Looking back, Danamichele sees how every class served a purpose in helping her build a successful career.

“I just happened to turn to a page, and on that page for that week, I wrote what I did,” she says. “Expert systems class canceled, database class, Mark Mazur budgeting assignment quiz or something like that.

“Those things that we were doing back then, rules-based expert systems and database design, were a critical foundation.”

Early Exposure

That critical foundation helped Danamichele build a career out of solving big business problems. And she was lucky enough to see such problem-solving in action early on.

While at CMU, she did an internship at Congress’ Office of Technology Assessment (OTA), which conducted large public policy studies on new or expanding technologies.

The study she did there, “Electronic Bulls and Bears Technology in U.S. Securities Markets,” examined technology use in stock exchanges.

“Here I am, this young CMU student flying all over the country talking to people about how they're using systems and technology on all of these stock exchanges,” she says. “I was interacting with people like Dick Grasso at the New York Stock Exchange and Bill Brodsky in Chicago and it was just incredible. What an incredible opportunity to watch the intersection of technology and public policy in action.”

That experience inspired her future career.
 

Patenting Progress

After graduating from CMU, Danamichele earned a master’s degree in operations research and decision sciences from the Wharton School of the University of Pennsylvania. She then accepted a job at Rosenbluth International, a corporate travel management company.

“I really wanted to apply my technology background to business or to public policy or something,” she says. “I wanted to solve big problems, like I saw these fellows at CMU doing.”

While at Rosenbluth, she invented a system, which was later a patented, to reverse the impact of airline yield management pricing, a strategy where airlines adjust ticket prices and seat availability to maximize revenue. By using Danamichele’s patented advanced technology system, corporations like Kodak and Intel were able to negotiate airfare pricing.

“It put them on a level playing field,” she says. “So not only did it save these corporations millions of dollars, but it also enabled our travel company to transition from a transactional business model to a management service, where our expertise and our patents and our technology were bringing value to the corporate travel program.

“I was able to invent the technology, but I was also able to experience the commercialization of it. That was incredible. It was exactly what I wanted. I wanted to see a big, meaningful business problem and apply advanced technology to solve it.”

Danamichele continued solving “big business problems” later in her career. As chief technology officer and senior vice president at Jackson Hewitt Tax Service, she led the deployment of machine learning in the call center, allowing the company to onshore jobs back to the U.S. from the Philippines. Under her leadership, Jackson Hewitt also received IRS approval for the industry's first electronic storage and signature, and invented the first self-service tax preparation application.

As general manager at Ancestry.com, Danamichele helped deploy advanced technology to the professional genealogy division, where users could hire an expert to do the research for them.

“We were using machine learning and we were even beginning to use some large language models for a lot of stuff because it was large-scale databases and searching,” she says. “Now, years later, the AI is really addressing some of those issues. But that was exciting and I was able to scale that division globally so I got even more global experience.” 

Busting Bad Bank Data

In 2023, Danamichele and her husband, Lester Dye, decided to combine their talents to start badbank.ai.

“We had a couple of small businesses going and were just so frustrated with the accounting systems and their inability to give you understandable knowledge about your transaction,” she says.

Lester, a Stanford engineer with extensive background in computer science, computational fluid mechanics and machine learning, left his Ph.D. program with venture funding to commercialize his thesis research. He has since founded multiple companies, applying advanced computational methods to challenges in fluid mechanics and finance. Recent years of experience in modern AI provided the foundation for the computational model powering Badbank.ai.

“We were like ‘Gosh, this could really help every single small business in the world who just needs to understand and see their expenses combined and aggregated and cleaned up,’” Danamichele says.

Since launching the company, Danamichele and Lester have helped small businesses around the country save money and reconcile their financial records. They are currently preparing for a new release, have patents pending in the U.S. and internationally, and are looking to apply the badbank technology on a global scale.

It’s one more “big business problem” that Danamichele is excited to tackle. And that CMU planner? It served as a reminder of the place that first inspired her to do so.

“It was fun to think about how lucky I've been and how so much of this really did start at CMU,” she says. “It was just fortuitous that I opened up that little planner. All of this stuff that I didn't realize at the time was going to be, for decades, so impactful to everything that I did.”