Customers and regulators are increasingly scrutinizing your Digital Onboarding procedure, and fraudsters are becoming more sophisticated. Verifying your online consumers’ real-life identities is an increasing problem and requirement for organizations across industries.
Europe’s new Digital Identity wallet offers inhabitants and companies a digital ID they can rely on, it acts as a tool which not only verifies and stores ID data but also enhances the application of the data for ease of use. The European Digital Identity will be held in a mobile phone wallet. This would make it easier to communicate important information in a timely and user-friendly manner at the discretion of the individual.
Perhaps you have recently seen some shocking statistics concerning the prevalence of identity theft, or perhaps you have a close friend who has gone through a terrible and stressful fraud situation. Even worse, you could already be familiar with the terrifying consequences of identity theft. Whatever the situation, you probably feel helpless to take any action to safeguard yourself. You’re not alone; this feeling is widespread.
According to a recent analysis, 17 million Ethereum transactions between Q4 2017 and Q1 2022 were associated with both criminal and licit operations. The overall cyber money laundering activities increased by 30% in 2021 compared to 2020, with hackers laundering a total of US$8.6 billion in cryptocurrencies.
Financial organizations employ the process of customer due diligence to gather and assess pertinent data about current and prospective clients. By analyzing data from many sources, it seeks to identify any possible risks to the financial institution associated with doing business with a certain organization or person.
In the context of digital onboarding, demographic features such as ethnicity, age, gender, socioeconomic circumstances, and even camera/device quality might affect the software’s capacity to match one face to a database of faces i.e. AI Bias. The quality and resilience of the underlying database in various sorts of surveillance might feed bias in the AI models. Biometrics are used in modern face recognition software to map facial traits from an image or video.
