Show Notes
Today's guest is Kelly Uphoff, Vice President of Data Science at Tala. Tala is a fintech company that develops an app that lets users bridge digital and cash ecosystems seamlessly to manage their finances. Kelly joins Emerj Senior Editor Matthew DeMello on today's show to discuss how AI and machine learning are driving financial inclusion for underserved populations. Throughout, she explains how Tala leverages alternative data to expand access to credit for individuals shut out of traditional financial systems. Kelly also shares how Tala's use of proprietary data and advanced AI tools, such as large language models (LLMs), is helping to identify creditworthiness in customers historically overlooked by legacy financial institutions. To access Emerj's frameworks for AI readiness, ROI, and strategy, visit Emerj Plus at emerj.com/p1.
More from AI in Financial Services Podcast
Product photography has long been one of e-commerce's biggest cost and speed bottlenecks, and generative AI is rewriting both sides of that equation. In this episode, David Cost, Chief Digital Officer at Rainbow Apparel Co, examines how generative AI is reshaping product imagery and video production for commerce teams. The conversation covers cost and speed gains, the risk of visual sameness across AI-generated creative, and how brands are rethinking model rights as they adopt digitally created models.
Enterprise AI investment keeps stalling before it reaches measurable business impact, and the reason is rarely the technology itself. In this episode, Sam Mantle, CEO at Lingaro, unpacks why data quality and ownership, not model capability, determine whether a pilot scales into something a CFO will call a win. The conversation covers how to diagnose a pilot headed for "pilot purgatory," a real-world example of using AI to resolve data-quality issues at scale, and the one practical step leaders can take this week to move from AI experimentation to impact. This episode is sponsored by Lingaro. In this episode, we cover why enterprise AI pilots stall before delivering measurable business impact, and what it takes to build the data foundation that lets AI scale.
A growing share of AI‑for‑CX guidance assumes a generic enterprise environment, but this episode surfaces the deeper operational friction that emerges when automation meets high‑stakes, highly regulated customer interactions.
AI is breaking down the traditional separation between technology leadership and people leadership, forcing enterprises to rethink how work is structured and how employees adopt new systems.
Enterprises rushing agentic AI into production are running it through approval gates, batch windows, and audit systems built for human speed — and the gap is where most operational risk lives. In this episode, Chris Caldwell, President and CEO at Concentrix Corporation, examines how machine-scale transactions break processes designed for human pace and why bounded digital delegates outperform unrestricted digital twins in the enterprise. The discussion covers compliance bots that check other bots, the cost reality of poorly tuned agentic agents, and what leaders need to stop doing if they want a defensible AI roadmap. Learn how to evaluate AI vendors by assessing leadership expertise, and why funding benchmarks can signal product maturity and stability, download our free PDF report, "5 Ways to Select the Right AI Vendor," at emerj.com/aiv2.