ARGOS Identity
ARGOS serves as a cutting-edge platform focused on AI-driven digital identity solutions. We are transforming the global landscape of identity experiences, impacting how individuals and organizations interact with their identities. Our mission is to develop crucial identity solutions that prioritize the safety and security of digital environments across the globe. With our services, we enable you to recognize anyone, no matter the location or time! Our commitment is to enhance the trust and reliability of digital interactions for everyone involved.
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iDenfy
An all-encompassing solution for confirming identities, detecting fraud, and ensuring compliance is now available. iDenfy employs a three-tiered approach to identity verification, safeguarding startups, financial institutions, online gambling platforms, streaming services, rideshare companies, and various other digital enterprises from identity fraud. This method effectively shields organizations from the most harmful types of identity fraud that can occur.
The platform provides an extensive range of fraud prevention tools, such as business verification, proxy detection, fraud scoring, and anti-money laundering (AML) screening, alongside ongoing monitoring and NFC verification, among other services to combat fraud. Since its inception prior to the establishment of AML, GDPR, and various fraud regulations, iDenfy has been at the forefront of the identity verification industry, mastering the complete verification process by integrating AI biometric recognition with meticulous manual checks to confirm the authenticity of users.
Utilize our ID verification software to potentially reduce identity verification expenses by up to 40%, as you will only incur costs for successful verifications. By employing iDenfy, businesses not only enhance their security measures but also streamline their operational efficiency.
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SHIELD
Prioritizing device-based fraud prevention through immediate intelligence and identification is essential.
With SHIELD's Device Intelligence, you can recognize which devices, users, and accounts are reliable while identifying those that pose a risk.
Ensure that fraudsters cannot deceive you—utilizing the globally recognized SHIELD DeviceID allows for accurate assessments of device reliability.
Gain an in-depth understanding of every user with live device signals and an ongoing risk assessment to eliminate blind spots, enhancing user experiences and driving growth.
Enjoy immediate insights without the hassle of extra codes, obtaining intelligence while safeguarding personal information.
You can also customize risk thresholds independently, as we offer comprehensive data and beyond.
Our transparent intelligence equips you with an all-encompassing perspective, helping you stay ahead of evolving fraud tactics.
Additionally, we synchronize real-time attack patterns on a global scale to ensure that you are always informed of the latest threats.
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RISK IDENT
RISK IDENT stands out as a premier software development firm specializing in anti-fraud solutions tailored for the e-commerce and telecommunications industries. Our proficiency in machine learning and data analytics sets us apart in the field. Among our flagship offerings are DEVICE IDENT Device Fingerprinting and FRIDA Fraud Manager, which tackle issues such as account takeovers, payment fraud, and fraudulent loan applications. Our sophisticated software solutions are designed to identify online fraud by swiftly assessing and analyzing a multitude of data points. We empower businesses with real-time insights that enable the preemptive prevention of fraudulent activities. With numerous accolades and a strong emphasis on data security, we believe the cornerstone of effective fraud prevention lies in a robust network that analyzes all pertinent data at remarkable speeds. By providing immediate identification of anomalies, we ensure that our clients stay one step ahead of potential threats. Our commitment to innovation drives us to continuously enhance our solutions and maintain our leadership in the industry.
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