In this episode 15 of Ctrl + Shifter, we sit down with Matti Junila, Head of Customer Success at ComplyAdvantage, to explore how AI is transforming customer success and financial crime prevention.

With years of experience in AI, machine learning, and customer service, Matti shares his expertise on how AI is improving fraud detection, reducing manual work, and helping businesses navigate compliance challenges. He dives into the rise of agentic AI, automating tasks traditionally handled by humans, and offers advice on adopting AI responsibly. Tune in to hear how AI is reshaping customer support in high-stakes industries.

Timestamp

01:57 - Matti's Background & Early career

04:45 - About ComplyAdvantage

07:47 - Leadership Challenges in AI-Driven Financial Crime Prevention

10:24 - AI Trends in Customer Support

19:26 - Decision-Making Principles for Responsible AI Adoption

22:28 - Strategic AI Adoption: From Evaluation to Scaled Impact

32:23 - Future of AI in Customer Support

35:08 - Advices on AI Adoption

There’s a short-term risk of doing an AI adoption and implementation when something goes wrong.

But there’s an even bigger long-term risk of doing nothing.

About Our Guest Speaker

Matti Junila

Head of Customer Success at ComplyAdvantage

He started out in computer science and have always been focused on AI and machine learning. Over the last 10+ years, he has helped build and scale tech startups, leading customer success teams and working closely across product, engineering, and commercial teams.

Our mission is to empower every business to eliminate financial crime. By harnessing AI, a unified platform, and an extensive partner ecosystem, we help customers turn compliance into a catalyst for growth, operational resilience, and enduring regulatory trust.
More than 3,000 enterprises across 75 countries rely on our end-to-end platform and the world’s most comprehensive financial crime risk intelligence. With full-stack agentic automation, we help organizations automate up to 95% of KYC, AML, and sanctions reviews, cut onboarding times by 50%, reduce false positives by 70%, and handle 7x more work with the same staff.

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