And why even today’s digital tools need a smarter, AI-first evolution

It’s past midnight. Sumit, 22, a data analyst, is applying for a digital credit card. Paperless onboarding. Seamless UX. Until the screen flashes:
“KYC incomplete.”

No explanation. No guidance. Just a dead-end.
For a generation used to one-click checkouts and 10-minute deliveries, 48 hours of waiting for “an agent to call” is a deal-breaker. And this isn’t an isolated glitch; it’s a symptom of how KYC has failed to keep pace with the digital world.

Financial institutions may have shifted from paper forms to apps and OTPs, but most “digital” KYCs are still analog at heart. They rely on outdated trust signals: a selfie matched to an ID, a document upload, a one-time code. Once revolutionary, these are now digital facades on legacy processes – friction-heavy for genuine users yet easy for fraudsters to bypass.

The pandemic accelerated the move to video KYC, a step forward then but strained today. Managing agents, bandwidth, and time zones at scale is inefficient, while fraud has evolved faster. With deepfakes, synthetic identities, and rented digital footprints, deception now looks alarmingly real. Fraudsters don’t need fake PAN cards anymore – just AI tools and a webcam.

The core issue: institutions have modernized interfaces, not trust frameworks. Systems verify documents but not intent; confirm faces but miss impersonation. Mule accounts and synthetic identities slip through easily. In 2025, these aren’t anomalies – they’re mainstream fraud tactics.

Speed alone is no longer a differentiator, and security without intelligence kills experience. The challenge now: How can institutions deliver both trust and seamlessness?

The answer lies in rethinking KYC as a living trust framework, not a compliance checklist. Modern KYC must be intelligent by design – understanding context, detecting anomalies, and evolving with threats.

AI-native KYC makes this possible.

• Passive liveness detection verifies depth and texture without user prompts.
• Deepfake detection embedded in onboarding filters out fake faces instantly.
• Behavioral biometrics analyzes how a user types or taps, assessing authenticity through micro-behaviors.

Beyond these, real-time risk engines can orchestrate trust dynamically – pulling identity, device, behavioral, and network data into a continuously updating trust score. This approach accelerates onboarding, reduces manual reviews, and minimizes false positives.

For users, it means faster access; for institutions, fewer fraud losses and better compliance.

KYC has long been seen as a necessary regulatory step. Today, it’s a strategic differentiator. The shift must move from static, one-time verification to systems that continuously build and reassess trust.

The key question isn’t “Can we verify this person?” but “Can we trust this person, right now?”

Trust is dynamic. It learns, adapts, and evolves – just like fraud. Moving from digital-first to AI-first isn’t a tech upgrade; it’s a mindset shift.

Because in a world of instant gratification, if your onboarding feels outdated, your users won’t wait for you to catch up.

About Author

Paritosh Desai is an experienced executive leader with a focus on developing innovative solutions for the industry.

He has 25 years of experience in heading up products, design and consulting for various industries with emphasis on data management and analytics, customer experience, organizational design, business intelligence and project execution.