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CogniLegit
Problem Statement
Rising Identity Fraud
Identity fraud, including the use of masks and deepfakes, has surged, costing global businesses billions.
Inadequate Security Measures
As per The Nilson Report (2022), a majority of financial institutions faced $32 billion in global fraud losses in 2021, with a substantial portion attributed to inadequate fraud prevention mechanisms, including biometric systems without liveliness detection.
User Experience and Accessibility Issues
Stringent verification processes can inconvenience users, impacting customer satisfaction and accessibility.
Regulatory Compliance Pressure:
Businesses face increasing regulatory demands to implement robust identity Verification measures.
Our Approach
Data Collection
Gather a comprehensive dataset that includes various types of images and videos, such as genuine human interactions, masked faces, deepfakes, and other spoofing attempts
Feature Engineering
Extract relevant features such as facial landmarks, motion cues etc. to enhance the detection power of the model.
Model Selection
Select and fine-tune deep learning models like CNNs for spatial feature extraction and RNNs for temporal analysis.
Training Techniques
Our AI algorithms will use transfer learning (pre-trained CV models) and improve accuracy by cross-validation.
Real-time Analysis
Integrate the trained model into live video streams for real-time tracking and authentication of individuals.
Our Solution
- Our liveliness detection solution verifies the authenticity of individuals in real-time, significantly reducing the risk of fraud.
- Advanced AI algorithms offer enhanced protection by accurately distinguishing between genuine and fake identities.
- Ensure seamless and user friendly verification, enhancing user experience without compromising security
Impact
- Our AI-powered Liveliness detection solution can lead to a decrease in identity fraud incidents, saving businesses up to 5% of their annual revenue in fraud-related losses.
- CogniLegit can enhance user onboarding journey, with a high satisfaction rate among users due to the streamlined and accessible verification process.
- Implementing liveliness detection can reduce the risk of biometric spoofing by 90%,according to a 2022 study by Biometric Research Group.
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