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Events

Interviews

From Proof of Concept to Industry-Leading Results

What It Really Takes to Scale AI in Financial Services

Events

Interviews

From Proof of Concept to Industry-Leading Results

What It Really Takes to Scale AI in Financial Services

Who Will Benefit Most

Senior financial crime and compliance leaders responsible for transactions screening, operational efficiency, and regulatory risk management, including:

Chief Compliance Officers (CCOs), Chief Technology Officers (CTOs), Money Laundering Reporting Officers (MLROs), Chief Financial Crime Officers, Heads of Financial Crime, Heads of AML and Sanctions, Heads of Financial Crime Operations, Compliance Directors, Financial Crime Transformation Leaders


A candid conversation between practitioners who have done it

Not once, but across decades and multiple institutions. No slide decks. No prepared talking points. Just an unscripted conversation about what actually works.

Whether you are evaluating AI for the first time or trying to scale what you have already deployed, this session offers the ground-level perspective that analyst reports cannot give you.

THE SPEAKERS

Practitioners. Not theorists.

THE SPEAKERS

Practitioners. Not theorists.

Markus Schulz

Chief Technology Officer

K2 Integrity

Martin Markiewicz

Co-founder and Chief Executive Officer

Silent Eight

Vlada Grebenykova

Chief Marketing Officer

Silent Eight

SESSION OUTLINE

A structured conversation, not a pitch

The session covers the full arc from evaluation through deployment to scale — with time spent on the operational and governance realities that most vendor conversations skip entirely.

SESSION OUTLINE

A structured conversation, not a pitch

The session covers the full arc from evaluation through deployment to scale — with time spent on the operational and governance realities that most vendor conversations skip entirely.

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THE STARTING POINT

What challenges drove the decision to act

How a high false-positive volume at manageable scale becomes an existential problem at enterprise scale — and how to recognise that inflection point before you hit it.

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EVALUATION CRITERIA

How to choose a technology partner — not a technology

Track record, speed of implementation, AI-native architecture, and willingness to work within constrained timelines. What a six-week deployment actually required.

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ARCHITECTURE IN PRACTICE

Screening + adjudication: how the two layers work together

Cast a wide net at matching, then let AI resolve the noise — reducing human workload from 100% to approximately 30% of matched alerts while maintaining full effectiveness.

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BUILDING TRUST

From QA oversight to autonomous closure

Why sandboxes cannot build institutional confidence — and the specific mechanism that allowed the team to progressively extend autonomy to the machine over weeks of production data.

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REGULATORY REALITY

Conversations with examiners and internal audit

How the regulatory posture on AI has shifted since 2024, what explainability means in examination, and why scale of error — not type of error — is now the primary scrutiny point.

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STRATEGIC FRAMING

Efficiency, effectiveness, and growth — where to start

A practical framework for senior compliance and technology leaders: where AI delivers first — operational capacity, control coverage, or business enablement.

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THE STARTING POINT

What challenges drove the decision to act

How a high false-positive volume at manageable scale becomes an existential problem at enterprise scale — and how to recognise that inflection point before you hit it.

Icon
Icon 2

EVALUATION CRITERIA

How to choose a technology partner — not a technology

Track record, speed of implementation, AI-native architecture, and willingness to work within constrained timelines. What a six-week deployment actually required.

Icon
Icon 2

ARCHITECTURE IN PRACTICE

Screening + adjudication: how the two layers work together

Cast a wide net at matching, then let AI resolve the noise — reducing human workload from 100% to approximately 30% of matched alerts while maintaining full effectiveness.

Icon
Icon 2

BUILDING TRUST

From QA oversight to autonomous closure

Why sandboxes cannot build institutional confidence — and the specific mechanism that allowed the team to progressively extend autonomy to the machine over weeks of production data.

Icon
Icon 2

REGULATORY REALITY

Conversations with examiners and internal audit

How the regulatory posture on AI has shifted since 2024, what explainability means in examination, and why scale of error — not type of error — is now the primary scrutiny point.

Icon
Icon 2

STRATEGIC FRAMING

Efficiency, effectiveness, and growth — where to start

A practical framework for senior compliance and technology leaders: where AI delivers first — operational capacity, control coverage, or business enablement.

Book a Strategy Conversation

Book a Strategy Conversation

Together we can explore three practical starting points tailored to your institution.


  • A scoping conversation - We walk through the efficiency, effectiveness, and growth framework discussed in this session, mapped directly to your institution's current screening and adjudication setup.

  • A transparency-focused Iris demo - See exactly how Iris explains its decisions in plain English, and understand why that explainability is the mechanism that allows institutions to progressively extend autonomy to the machine with confidence.

  • A readiness assessment - Honest conversation about where you are in the build vs. buy decision, what your natural upgrade cycle looks like, and what a phased deployment could realistically deliver for your team.