In this episode of CAIO Connect, host Sanjay Puri sits down with Abhishek Mittal, EVP and Chief Product & AI Officer at AML RightSource, for a deep and engaging conversation on how AI is transforming the fight against financial crime.

From building AI systems that thrive on imperfect data to pioneering “digital FTEs,” Abhishek shares a pragmatic view of what it takes to make AI work in the real world — where innovation, governance, and human expertise come together to drive meaningful, enterprise-scale change.

💡 5 Key Takeaways:
🔹 AI with Imperfect Data: Why waiting for “perfect data” is a trap — and how to iterate your way to AI success.
🔹 Synthetic Data Evolution: How synthetic data is training smarter models and preparing them for unseen scenarios.
🔹 Financial Crime as a Global Issue: If financial crime were a country, it’d have the world’s 7th largest GDP — and AI could be its toughest opponent.
🔹 Digital FTEs & Agentic AI: How AI agents and human experts are working side by side to redefine efficiency and decision-making.
🔹 Innovation at Scale: Abhishek’s 5-step framework for turning bold ideas into commercial AI success.

If you enjoyed this conversation, don’t forget to like, share, and subscribe for more insights from global AI leaders shaping the future of enterprise transformation.

Resources Mentioned:
https://www.linkedin.com/in/abhishek-mittal-7115348/

Timestamps:
00:00 — Introduction: Financial crime as “7th largest GDP”; podcast begins
00:30 — How AI is transforming anti-money laundering (AML)
01:10 — The ethos of AML RightSource: “Financial crime fighter” mindset
02:45 — Global scale and complexity of financial crime
04:35 — Crypto, digital money & regulatory challenges
07:00 — Elder abuse scams and the role of banks in prevention
09:00 — Education, awareness, and the importance of policy
11:40 — Data doesn’t have to be perfect—how to iterate AI with imperfect data
15:00 — Synthetic data, quick wins & scalable solutions
18:20 — Guardrails for AI with imperfect data: “cost of being wrong” and risk metrics
21:20 — Human-in-the-loop and deterministic quality checks
23:00 — Human expertise as “moat”; why experience in using AI matters
26:30 — Workflow integration: Why domain experts’ role changes in the agentic AI era
28:45 — Abhishek’s definition of agentic AI & digital FTEs (AI agents)
31:00 — Product innovation: 5-stage process to commercialise ideas (ideation, validation, experimentation, incubation, commercialisation)
33:00 — Measuring ROI from innovation: board-level, commercial, and activity metrics
34:30 — Rapid-fire Q&A: Open source, explainability, speed vs. perfection, AI’s biggest risks

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