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

I am a security leader with over 15 years of experience in payments and digital identity. At Hooli/MIA, I led teams building device-agnostic biometric payment rails, integrating multimodal authentication (behavioral, facial, voice, keystroke dynamics) with advanced liveness detection and risk-based orchestration. These solutions cleared PCI DSS and PSD2 SCA standards while enhancing conversion, and were deployed globally under strict privacy-by-design and zero-trust frameworks.

Q2. With the behavioral biometrics market projected to reach $8.24 billion by 2033 at 21.5% CAGR and AI-enabled biometrics reaching $49.40 billion by 2032 at 7.88% CAGR, which specific segments within your expertise offer the highest potential?

• Payments & fintech account defense: ATO prevention, mule detection, and high-risk wire protection.
• Continuous workforce authentication: especially for high-privilege access.
• IoT and edge form factors: kiosks, POS, travel, and unattended retail.
• Orchestration platforms: unifying behavioral, device, and identity signals.
• Privacy-preserving analytics: federated learning and differential privacy to enable global-scale improvements without moving raw PII.

Q3. Which industry verticals and geographies are showing the fastest adoption of AI-powered behavioral authentication, and what can you share some use cases for them?

• Financial services (EU/US/BR): frictionless SCA and fraud prevention.
• Travel & hospitality (US/EU/MEA): airport-style continuity from check-in to boarding.
• iGaming & digital goods (UK/LatAm): compliance and bot/fraud suppression.
• Healthcare (US/EU): clinician re-authentication on shared systems.
• Public sector/critical infrastructure (EU/APAC): privileged access with behavior-based step-up.

Q4. How are evolving privacy regulations and data sovereignty laws shaping the design and deployment of AI-powered biometric authentication solutions globally?

• Data minimization and purpose binding.
• Data localization/sovereign deployments for GDPR, Schrems II, India, and LatAm.
• Strong governance: audit trails, drift monitoring, and bias testing.
• Privacy-enhancing tech: federated learning, secure enclaves, and feature hashing.
• Verified PAD/liveness attestations required in procurement.

Q5. How is the integration of biometric authentication with emerging digital identity frameworks influencing enterprise buying decisions?

Enterprise buyers now prefer interoperable identity stacks. Passkeys/FIDO2 form the base, behavioral biometrics ensure continuous assurance, and verifiable credentials provide attribute proofing. This drives shorter RFPs, larger platform deals, and reduces reliance on fragmented point solutions.

Q6. In what ways are AI and machine learning advancing continuous authentication beyond initial login, and how does this impact overall security and user experience?

Advances include multimodal fusion, sequence modeling, and adaptive thresholds. These reduce unnecessary step-ups while improving fraud detection. Outcomes: ~30–60% fewer friction events for legitimate users, lower SMS/OTP costs, and improved overall UX without compromising MFA strength.

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

The critical question I would pose: “Can you prove your risk-reduction outcomes are causal and portable?” Specifically, demonstrate blinded A/B tests across customers and geographies with measurable impact on ATO prevention, conversion rates, PAD efficacy, and transparent data-governance frameworks.