# EP 44: Human-Centered Credit - Building Explainable AI for Lending in an Agentic World

Page: https://stenobird.com/podcast/data-science-with-sam-4345646/ep-44-human-centered-credit-building-explainable-ai-for-lending-in-an-agentic-world
Text version: https://stenobird.com/podcast/data-science-with-sam-4345646/ep-44-human-centered-credit-building-explainable-ai-for-lending-in-an-agentic-world.md
Podcast: [Data Science With Sam](https://stenobird.com/podcast/data-science-with-sam-4345646)
Published: 2026-07-04T19:53:16+00:00
Episode link: https://rss.com/podcasts/data-science-with-sam/3006404
Audio file: https://content.rss.com/episodes/395137/3006404/data-science-with-sam/2026_07_20_13_46_50_f4b0f8bc-6e66-443c-87cf-35c83c2512ba.mp3
Processing state: not_requested
JSON: https://stenobird.com/v1/public/podcasts/data-science-with-sam-4345646/episodes/ep-44-human-centered-credit-building-explainable-ai-for-lending-in-an-agentic-world
Duration seconds: 1306

## Resource

We are letting AI make life-changing financial decisions without requiring it to explain itself. The CFPB says 'insufficient information' is no longer an acceptable reason to deny a loan. The EU AI Act classifies credit scoring as high-risk. And more than half the US workforce - gig workers, fractional leaders, solopreneurs - is still scored by models built for a 1950s economy. Tamara Laine is the Founder and CEO of MPWR AI and an Emmy Award-winning investigative journalist turned fintech executive. Her reporting on ethical AI at Amazon and Northrop Grumman earned her an Emmy. Her work at MPWR - building explainable, policy-bound AI for the lending lifecycle - has earned her a seat in the Fintech Sandbox. IN THIS EPISODE: ▪ How Tamara's path from ballet to journalism to fintech all follows the same thread: spot a problem, find the expertise to solve it, create change ▪ Why half the US workforce is now a gig worker, creator, Gen Z worker, or thin-filed borrower - and why FICO models were never built to see them fairly ▪ What MPWR AI actually does: six policy-bound agents across the full loan lifecycle, pulling hundreds of data points to help lenders say yes more often ▪ The core architectural principle: AI does the work, deterministic models make the decisions - because LLMs can be biased and engineered to produce answers that are simply not true ▪ The two-button audit system: a decision audit and a bias audit, immediately available to any compliance team ▪ Patent-pending architecture: agents operate in defined information buckets — if the information isn't there, the system cannot answer and cannot hallucinate ▪ How MPWR measures whether it's actually expanding access: higher acquisition rates, lower defaults, reduced manual work - all benchmarked against lenders' own…

## Actions

- request_transcript: `POST https://stenobird.com/v1/public/podcasts/data-science-with-sam-4345646/episodes/ep-44-human-centered-credit-building-explainable-ai-for-lending-in-an-agentic-world/transcription-requests` — Idempotently request low-priority transcript generation for this episode.
- read_markdown: `GET https://stenobird.com/podcast/data-science-with-sam-4345646/ep-44-human-centered-credit-building-explainable-ai-for-lending-in-an-agentic-world.md` — Read the agent-friendly Markdown representation of this episode resource.

A page view does not enqueue transcription. Agents should invoke `request_transcript` explicitly when they need this episode processed.

## Transcript

Full transcripts are not published on public pages unless there is a clear rights basis.