DEEPFAKE VOICE DETECTION

AI consultancy and outsourcing

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Client
Enterprise Security Partner
Industry
FinTech
Project Overview

Voice-based fraud has become one of the fastest-growing cybersecurity threats. Executives and customers are being impersonated through AI-generated voices, leading to financial losses and reputational damage. Cube developed an AI-powered detection system that identifies synthetic voices in real time. Using deep neural networks and spectrogram analysis, it flags cloned speech, assigns instant risk scores, and integrates directly into existing workflows across finance, telecom, and healthcare, securing every call and restoring customer trust.

_________CLIENT DETAILS

Restoring Trust in Digital Voice Communication

We built an AI-driven verification system that detects synthetic voices instantly, helping enterprises prevent fraud, protect customers, and maintain secure, compliant interactions.

_________PROBLEM

When sound becomes a threat

Deepfake voice scams exploit human trust to breach security and trigger financial fraud. Traditional authentication is too slow, manual, and easy to bypass, exposing organizations to rising risk in every customer interaction.

_________SOLUTION

We esigned a real-time AI verification layer that connects to telephony, VoIP, and contact center systems, operating silently to authenticate every voice without changing how agents or customers interact.

AI Detection Engine – Deep learning models trained on thousands of authentic and synthetic voices, achieving 95%+ accuracy in real-world conditions.
Instant Risk Scoring – Each call is analyzed and classified in seconds with transparent risk metrics.
Workflow Integration – Seamlessly connects to CRM, KYC, and fraud platforms via secure APIs.
Compliance Ready – Built with enterprise-grade encryption, access control, and GDPR alignment.

Key Differentiators

  • Proven Accuracy: Detects cloned, replayed, and AI-generated voices with industry-leading precision.
  • Zero Friction: Verifies authenticity in the background — no workflow changes.
  • Rapid Integration: Cloud-agnostic APIs deploy easily across enterprise systems.
  • Operational Impact: Reduces manual verification by up to 90%, saving time and cost.
  • Adaptive Security: Continuously learns to detect emerging AI-generated voice patterns.
_________RESULTS
Results: 30–50% reduction in voice-fraud losses within 12 months. 90% faster verification across global call centers. Increased customer trust and compliance confidence. “A single AI layer now stops millions in potential fraud losses every year.”
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Conclusion

AI-generated voices are nearly indistinguishable from real ones creating new challenges for trust and identity. Our solution detects deepfake voices in real time, helping enterprises secure every interaction, prevent fraud, and maintain confidence in digital communication.