Sumsub
Sumsub is a full-cycle verification platform that secures every step of the user journey. With Sumsub’s customizable KYC, KYB, AML, Transaction Monitoring and Fraud Prevention solutions, you can orchestrate your verification process, welcome more customers worldwide, meet compliance requirements, reduce costs and protect your business.
Sumsub achieves the highest conversion rates in the industry—91.64% in the US, 95.86% in the UK, and 97.89% in Hong Kong—while verifying users in less than 50 seconds on average.
Sumsub’s methodology follows FATF recommendations, the international standard for AML/CTF rules and local regulatory requirements (FINMA, FCA, CySEC, MAS, BaFin).
Sumsub has over 2,000 clients across the fintech, crypto, transportation, trading, e-commerce and gaming industries including Bitpanda, Wirex, Avis, Bybit, Huobi, Kaizen Gaming, and TransferGo.
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DeepDetector
DeepDetector is a deep learning network designed and trained to recognize AI-generated or AI-manipulated faces. DeepDetector can be seen as an artificial neural network designed to spot forgeries and traces generated by computers. It serves as a critical tool in verifying identities and preventing fraud. DeepDetector is especially adept at detecting AI-generated content, making it an essential asset in the fight against deepfakes. Through the integration of biometric systems, it ensures the authenticity of documents and safeguards the integrity of user identities, supporting KYC processes. Get quick and reliable identification of deepfake content in real-time with our accuracy rate of up to 99% and lightning-fast analysis time of just 1 second. Our flexible API integration empowers you to seamlessly customize and integrate our deepfake detection solution into your existing identity verification systems.
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FakeCatcher
Pioneered by Intel, the FakeCatcher deepfake detector analyzes “blood flow” in video pixels to determine a video’s authenticity in milliseconds. Integrated detection in editing software used by content creators and broadcasters. Detection as part of a screening process on user-generated content. Democratized deepfake detection via a common platform, enables any person or entity to confirm the authenticity of a video. Deepfakes are synthetic videos, images, or audio clips where the actor or the action of the actor is not real. ost deep learning-based detectors look at raw data to try to find signs of inauthenticity and identify what is wrong with a video. In contrast, FakeCatcher looks for authentic clues in real videos, by assessing what makes us human— subtle “blood flow” in the pixels of a video. When our hearts pump blood, our veins change color.
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