Liveness Detection in Banking: Case Studies & ROI

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Liveness detection is presented as a key defense for banks facing growing presentation attacks, deepfakes, and other identity spoofing methods that traditional document checks may not catch. The text cites a Southeast Asian bank that reportedly reduced new-account fraud from 15% to under 2% after adopting passive liveness detection, saving an estimated $500,000 annually, and a European neobank that reduced fraudulent transaction attempts by 60% through active checks requiring randomized user actions. It argues that return on investment includes lower fraud losses, fewer manual reviews, improved customer experience, and stronger KYC/AML compliance, while recommending solutions that balance accuracy, speed, usability, integration, and scalability. Didit promotes its own combined passive and active liveness offering, claiming iBeta Level 1 certification, 99.9% accuracy, customizable workflows, real-time monitoring, analytics, and API, SDK, and hosted integration options.

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