AI Thoughtmakers

AI is making fraud smarter. But it’s also making fraud detection faster, sharper, and more intelligent than ever before.In this episode of AI ThoughtMakers, we sit down with Gaurav Porwal, Principal Technical Consultant at GeekyAnts, to explore how AI is reshaping the future of fraud prevention in banking and financial systems.From deepfake-enabled KYC frauds to biometric authentication, liveness detection, AI-powered security systems, and the growing race between fraudsters and financial institutions — this conversation breaks down the real-world challenges enterprises face in the AI era.Key topics covered:• How deepfakes are changing financial fraud• Why traditional KYC systems are no longer enough• AI vs fraudsters: who is winning?• The future of passwords, biometrics, and digital identity• How financial institutions use AI to detect fake identities• Why human verification still matters in AI systems• The role of compliance, security, and trust in AI-powered finance“If attackers are evolving with AI, financial institutions are evolving faster with data.”Watch the full episode to understand where AI security is headed next.Connect with Gaurav Porwal & PremLinkedIn -   / gaurav-porwal-811488118  LinkedIn -   https://www.linkedin.com/in/premgoswami/

In this episode of AI ThoughtMakers, Sarika Gautam, Principal Technical Consultant, Geekyants, breaks down one of the biggest gaps in modern AI product development: why AI prototyping tools fail when enterprise-grade security and trust enter the picture.Today’s AI tools can generate polished applications in minutes. But enterprise systems are not judged by how good the demo looks. They are judged by security, scalability, auditability, and trust.This conversation explores why critical enterprise features like SSL, RBAC (Role-Based Access Control), and audit logs remain extremely difficult to generate reliably using AI-first prototyping tools.Using real-world examples from platforms like Slack and Okta, Sarika explains why enterprise products succeed not because they are flashy, but because they are secure, reliable, and trusted.The discussion also uncovers the hidden risks teams often ignore while moving fast with AI-generated products:Why SSL and RBAC are far more complex than they appearThe overlooked importance of audit logs in enterprise systemsWhy AI-generated demos create “false completeness”Security risks in AI-assisted product developmentTechnical debt created by fast AI-generated systemsThe difference between presentation-ready and production-ready productsWhy enterprise trust cannot be generated with prompts aloneIf you’re building AI products today, this episode raises one important question: Are you building something that only looks impressive, or something enterprises can actually trust?Connect with Sarika Gautham & PremLinkedIn -   / sarika-gautam-047749238  LinkedIn -   https://www.linkedin.com/in/premgoswami/