Q1. Could you start by giving us a brief overview of your professional background, particularly focusing on your expertise in the industry?

I have 32 years of experience, over 18 years in FinTech, RegTech, and fraud-risk management, working with regional and international banks on risk frameworks, KYC/AML programs, AI-driven transaction monitoring, and advising regulators and investors on compliance technology and vendor assessments, as well as setting up governance frameworks.

Q2. Where do you see the next wave of RegTech consolidation driven by regulatory pressure and the rising cost of compliance?

Consolidation will focus on solutions that reduce compliance costs:

• Multi-jurisdiction regulatory reporting
• Real-time transaction monitoring and orchestration
• Advanced digital identity platforms and end-to-end compliance ecosystems

Regulatory pressure and rising operating costs are the main drivers.

Q3. In your view, which regulatory changes in the next 12–24 months will materially increase fraud-mitigation spending across banks and fintechs?

Fraud risk is mitigated by key triggers, including shorter SAR/STR filing windows, AI model transparency requirements, stronger consumer protection rules in digital payments and BNPL, continuous sanctions updates, and new operational resilience expectations.

Q4. Which fraud categories will see the largest budget increases from banks and fintechs in 2025–2027, and what is driving those allocations?

Top areas: Account takeover, synthetic identity fraud, mule-account networks, BNPL and application fraud, and deepfake-enabled social engineering — driven by digital growth and the accessibility of AI tools to attackers.

Q5. Based on your experience, how are banks currently detecting and mitigating AI-driven fraud threats, and which technologies have proven most effective in real-world deployments?

Banks rely on hybrid detection (rules + ML + behavioral analytics), device intelligence, graph-based network detection, adaptive risk orchestration, adversarial testing, and deepfake/voice-spoofing detection. Effectiveness improves when fully integrated into a single risk platform.

Q6. In your opinion, which banks are building the strongest competitive edge through deep AI/RegTech partnerships, and which vendors are most likely to gain significant share—or lose it—as these integrations scale?

Banks that form deep, data-sharing partnerships with RegTech vendors secure the greatest competitive advantage. The most successful vendors are those offering scalable, end-to-end platforms with transparent and explainable models.

In contrast, vendors relying on narrow point solutions—especially those with high integration costs and limited model-governance capabilities—are likely to lose ground as the market evolves.

Q7. If you were an investor looking at companies within the space, what critical question would you pose to their senior management?

“What defensible data, integrations, or model assets do you own that cannot be replicated within 12–18 months?”

This includes churn metrics, time-to-value, integration footprint, and regulatory readiness.