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Why Truth Beats Hope in Banking

Most AI failures don’t come from the model—they come from the data feeding it.

In this episode of the Data Faces Podcast, Tina Chace, VP of Product Management at Solidatus, speaks with David Sweenor, Founder of TinyTechGuides and host of the podcast, about why incomplete lineage, missing context, and silent upstream changes quietly undermine AI systems long before anyone notices.

Tina shares lessons from deploying AI and machine learning in major banks, breaking down how column-level lineage and business context prevent cascading failures across systems, teams, and decisions.

Key Takeaways:

  1. Why 90% of AI production issues trace back to data quality problems.
  2. How technical and business lineage work together to build trust.
  3. Why column-level tracking exposes the hidden transformations behind every metric.
  4. How visibility without control increases anxiety across data teams.
  5. Where organizations should start to get quick wins without “boiling the ocean.”

Listen to the Podcast Here on Spotify: https://open.spotify.com/show/6SmGkQGvZQSAT1O7g1l2yF

Listen to the Podcast Here on Apple Podcasts: https://podcasts.apple.com/us/podcast/data-faces-podcast/id1789416487

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