[09-17]verify identity online-selfie verification

METHOD OF ESTABLISHING IDENTITY VALIDATION BASED ON AN INDIVIDUAL'S ABILITY TO ACCESS MULTIPLE SECURE ACCOUNTS

Date:2021-09-17

aml & cft

Author:customer screening in banking    transaction monitoring rules examples

Keywords:enhanced due diligence kyc,    biometric details,    stripe id verification,    verifying identity over the phone,    id verification api,  a data breach

Description:

LiveNet: Improving Features Generalization for Face Liveness Detection using Convolution Neural Networks
In view of iris liveness detection of feature extraction,this paper proposes an iris liveness detection algorithm based on deep Convolutional Neural Network( CNN). Three modes of iris regions including normalization,block normalization and cutting directly are used to preprocess iris image,and they are suggested as the input of CNN for extracting features,then genuine and fake irises are identified with trained classifier. Experimental results show that this algorithm can learn the hidden characteristics of iris image automatically,make it more discriminative between genuine and fake iris feature,and it achieves above 96. 72% accuracy on ND-Contact and CASIA-Iris-Fake database.
The article seeks to investigate the relationship between artificial intelligence and fraudulent claims in the inclusive insurance sector in developing countries. Although low-income cover has been classified as an important tool to combat poverty, fraudulent claims continue to escalate and is more a serious threat to the low-income cover market sustainability as fraudsters seem to be a step ahead of the game. Through a review of literature that has flagged to be scarce, the author advances the hypothesis that artificial intelligence is more likely to be successful where the increased use of online purchases of inclusive cover (micro-insurance), high cost of identifying claims fraud, lack of data and resources experienced by the providers of inclusive cover amongst others, are available. The study's drive is predicated on the argument that although with the advances of computing techniques and technology, artificial intelligence systems can be employed to reduce the frequency and severity of fraudulent claims. Despite some identified challenges, the findings reveal that leveraging use of artificial intelligent systems in the low-income cover market could promote the effective sustainability of the inclusive cover niche market as it is an uncertain profit business by nature of its low premium income and high transaction cost compared to the regular insurance market. Finally, the author points to some possible ways for combating fraudulent claims occurrences through the effective use of artificial intelligence systems in the midst of Industry 4.0.

Similar Articles