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Episode summary

Community banks and credit unions face growing pressure to digitize—but many are underserved (or boxed in) by the current fintech market. Adam Turmakhan explains what institutions stand to gain with modern data and AI, what they risk by delaying, and how vendor models that take control of customer data can undermine long-term competitiveness.
American Bankers Association+1

About the guest

Adam Turmakhan is the CEO & COO of TurmaFinTech, a fintech focused on customer data platforms and data-driven growth for community banks and credit unions. He holds a Master’s in Data Science (Boston University) and a Bachelor’s in Accounting and Finance Management (Northeastern University).
turmafintech.com+1

What you’ll hear in this episode

• Why community banks’ “risk-averse” posture can become a competitive vulnerability
• Why data governance is the foundation for any credible AI strategy
• A practical framing: build a data layer, then deploy AI for defined business outcomes
• Where fintech partnerships go wrong: data control, lock-in, and monetization leakage
• What “success” looks like: measurable adoption, growth, retention, and efficiency gains

Highlight reel (based on the Schwab Network segment captions you provided)

• 03:10–04:20 — TurmaFinTech’s platform structure: data foundation first, then AI/ML objectives
• 04:30–04:55 — “Community panel” concept: targeted customer outreach driven by model outputs
• 05:09–06:05 — A concrete success story and measurable KPI improvement
• 07:19–07:33 — Go-to-market approach: free six-month pilot to prove operational value
• 08:00–10:00 — Data governance and the core warning: don’t lose ownership/control of customer data
• 10:00–11:10 — The forward vision: becoming a standard “data layer” for community institutions

Notable quotes (short excerpts)

• “The first component is the data warehouse… we take their data and structure it so it’s possible to work with.”
• “By default, we have four objectives… deposit growth, churn prevention, cross-sell/up-sell, and default prevention.”
• “We give a free six-month pilot… so they can see and taste the product before pricing becomes the main discussion.”
• “We want the community bank to own the data… instead of losing the opportunity to monetize it.”

Discussion prompts (if you run a longer Financial Forward interview)

• Where do community banks overestimate the risk of digitization—and underestimate the risk of standing still?
• What should banks require, contractually and operationally, to preserve data rights and portability?
• What are the first “low-risk wins” you’d prioritize in the first 30–90 days?
• What does a mature data governance model look like for a small team with limited expertise?
• What’s the biggest misconception about “AI for banks” that you encounter?

Resources (links)

Guest/Company reference points

More from Jim:
LinkedIn: https://www.linkedin.com/in/mccarthyhatch/
https://www.mccarthy-hatch.com/