Delighted to be in Kansas City this week for the TELECOMMUNICATIONS RISK MANAGEMENT ASSOCIATION meeting!
I’m here for a special fireside chat with Brian Newcomb, who leads credit risk at AT&T. Brian’s team has been at the forefront of modernizing telecom credit risk strategies using machine learning—and doing so in ways that make more money and do more good.
As the Founder and CEO of FairPlay I’ve spent the last few years helping banks and fintechs adopt AI to make smarter, more inclusive credit decisions. But over the past year, we’ve had the privilege of working with a new kind of client: telcos.
And let me tell you, telcos have surprised us.
Telcos have some of the most sophisticated credit strategies we’ve seen—rivaling top-10 banks and the most sophisticated fintechs. But what really blew my mind?
Telcos are the OGs of alternative data.
Long before open banking, there was NCTUE.
And unlike many financial institutions, telcos have mastered the art of blending risk assessment with great customer experience.
This learning journey—from financial services to telecom—has been eye-opening. And today’s conversation with Brian was a chance to dive deeper into that transition.
We explored:
– How AT&T leveraged machine learning to modernize their credit decisioning stack
– What data sources and features moved the needle (spoiler: alternative data plays a starring role)
– How they measured success with real-world outcomes
– The work they’ve done to ensure fairness, explainability, and organizational readiness
Our goal is to equip telecom risk leaders with solutions to modernize their own credit practices in fair, responsible, and effective ways.
If you’re at TRMA, come say hi!
And if you’re curious about how FairPlay is helping telcos adopt machine learning and alternative data in smarter, fairer ways—let’s talk.
