Rethinking Trust in the GenAI Era with Mahi Sethuraman
How do leaders navigate the delicate balance between rapid innovation and maintaining consumer trust? This question sits at the heart of a fascinating conversation on the Signal to Noise Podcast between Mahi Sethuraman, Vice President of Consumer Engineering at Credit Acceptance, and Kyle Langworthy, Partner and Head of AI, ML, and Data Practice at Riviera Partners.
Mahi’s career spans two decades across American Express, Ally, Affirm, and now Credit Acceptance, giving her a front-row seat to the evolution of consumer trust in financial technology, from the early days of eCommerce skepticism to today’s uncharted world of generative AI.
In this episode, Mahi shares insights on why trust is once again being tested, why collaboration matters more than “10x engineers,” and how leaders can remain grounded while moving at the speed of AI.
From “Never Put Your Card Online” to AI-Driven Decisions
Trust has always been the invisible currency of financial services. In the late 1990s and early 2000s, consumers resisted entering credit card details online. Banks and fintechs responded with fraud detection, multifactor authentication, and identity protection tools. Gradually, trust was earned, and eCommerce became second nature.
Fast forward to the mobile era: consumers didn’t just adopt smartphones; they demanded seamless mobile-first experiences. “The earliest signals for me were how quickly consumers pivoted to mobile as a form factor and channel. Even when we were still predominantly web-based, usage shifted almost immediately after the first iPhone.”
That adaptability is what gives her confidence that consumers will adopt AI-driven services if companies safeguard their interests. The challenge now is that the very signals of trust, like voice authentication or biometrics, can be spoofed with generative AI.
We are at the cusp of testing what trust means to the consumer, yet another time.
Building Data-Driven Fluency
Mahi’s passion for data was the pivot point in her career. At American Express, she took a leap into a VP role leading finance data engineering, even though most of her background had been in digital consumer experiences. It wasn’t an obvious fit, but she influenced her way into the opportunity by painting a vision for what data transformation could look like.
That risk paid off. Her team eventually stood up systems that processed massive volumes of AR and AP data in hours, transforming the company’s ability to make C-suite investment decisions.
This experience shaped how she now leads teams: not as pure technologists chasing the shiniest new ML platform, but as business partners fluent in KPIs, metrics, and impact.
For modern fintech leaders, technical chops alone aren’t enough. Data fluency is the differentiator.
The Myth of the 10x Engineer
In an industry that celebrates “10x engineers,” Mahi offers a contrarian take. “Real complex problems require collaboration.” While high-impact individuals can move the needle, building cultures that unlock the potential of every engineer is more sustainable.
Her organizational design philosophy is simple but powerful:
- Start with clarity of vision. A three-to-five-year north star aligns teams beyond short-term shifts.
- Foster shared purpose. Teams that understand why their work matters collaborate more effectively.
- Nurture learning. Good talent gets better with time; great talent learns faster and connects the dots more effectively.
- Leaders clear roadblocks. Leadership isn’t about being the hero; it’s about enabling the team organism to thrive.
She likens organizations to living organisms: adaptive, evolving, and dependent on every part functioning together.
The Noise vs. the Signal
With generative AI moving at a breakneck pace, leaders face a new kind of noise. Daily headlines trumpet new models, tools, and releases, but keeping up with every announcement can be paralyzing.
Mahi tunes out the hourly cycle and instead looks for macro signals. For instance, in subprime auto financing, she watches how consumers adopt mobile apps and interact with AI-driven repayment bots. Early adopters of mobile channels have proven more profitable, offering both efficiency gains and trust-building opportunities.
Her advice to aspiring fintech leaders? Get hands-on with new technologies. Just as doctors constantly update their knowledge with new research, software leaders must experiment directly with emerging tools.
Final Thoughts
The story of fintech is the story of trust, first in the web, then in mobile, and now in AI. Each era challenges leaders to rebuild that trust in new ways.
Mahi Sethuraman’s journey reminds us that while technologies change at lightning speed, the fundamentals of leadership don’t: clarity of vision, courage to take risks, and commitment to collaboration.
As the Gen AI era unfolds, the leaders who succeed will be those who can cut through the noise, tune into the signal, and build trust one interaction at a time.
Mahi’s Background
Mahi Sethuraman is the Vice President of Consumer Engineering at Credit Acceptance, bringing two decades of experience in building financial technologies that serve millions of consumers. With a vast background in fintech leadership, including executive roles at Affirm, Ally, and a 15-year tenure at American Express, Mahi has been at the forefront of digital transformation in financial services. Her expertise spans consumer banking, digital payments, data engineering, and AI implementation in financial services.
Listen now: Singal to Noise Episode 7: Rethinking Trust in the GenAI Era with Mahi Sethuraman
