Identity Verification and Artificial Intelligence: Crucial Insights for Businesses
Artificial Intelligence (AI) is transforming the identity verification (IDV) landscape, significantly improving precision in client identification and document of identity verification. This transformation is influenced by various regional regulations, driving innovation, and imposing new compliance burdens on developers and providers.
In the European Union (EU), the AI Act classifies biometric and document-verification AI as high-risk applications, mandating robust risk-management systems, transparency, and post-market monitoring. The eIDAS 2.0 regulation further requires digital identity wallets to meet high assurance levels and obliges service providers to accept cross-border wallets, harmonizing standards across member states. These rules compel companies to implement advanced privacy-preserving techniques, such as on-device biometric matching, to comply with strict data protection requirements while maintaining security. The GDPR remains a cornerstone for privacy, ensuring individuals retain control over their personal data. As a result, EU regulations are driving both innovation in AI-powered IDV and a global “Brussels Effect,” where multinational companies adapt their solutions to meet European standards.
In contrast, the United States lacks a unified federal privacy law, relying instead on sector-specific regulations and state-level initiatives like the California Consumer Privacy Act. Federal discussions, such as the White House’s voluntary AI Bill of Rights, have not yet resulted in comprehensive national standards. This patchwork approach allows for rapid innovation but can create inconsistencies in privacy protections and compliance obligations.
China's approach balances extensive government use of AI for surveillance with new privacy laws like the Personal Information Protection Law, which restricts corporate data use but does not limit state surveillance. This creates a distinct environment where private-sector IDV solutions face legal constraints, but government applications operate under different rules.
AI-driven IDV now emphasizes multi-layered defenses, combining advanced document forgery detection, biometric authentication, and liveness checks to combat both traditional fraud and AI-generated deepfakes. AI streamlines digital onboarding by rapidly verifying identity documents and flagging anomalies, reducing manual effort and human error while maintaining stringent KYC/CDD compliance. Machine learning also enhances ongoing risk monitoring by detecting suspicious transaction patterns. Regulations like the GDPR and AI Act incentivize privacy-preserving architectures, such as storing biometric templates locally on user devices rather than in centralized databases.
In some jurisdictions, such as the UK, certification is required for solutions to display a “Trust Mark,” ensuring adherence to national standards and fostering consumer confidence. The EU AI Act will be fully applicable in August 2026, with intermediate stages offering additional guidance to businesses to adapt their systems by August 2027.
Future technological advances in identity verification, such as China's DeepSeek model, will continue to transform the market and accelerate the creation of more specific regulations. For businesses, success now depends on integrating advanced AI capabilities with rigorous compliance and ethical practices. Regula, for instance, ensures full compliance with existing regulations like GDPR and the EU AI Act in its Identity Verification Solutions, Regula Document Reader SDK and Regula Face SDK. Regula is here to help businesses understand and adapt to the current requirements of AI use in their operations, and offers assistance for questions about AI use in their SDKs.
In the rapidly evolving software industry, the finance sector is incorporating advanced AI technologies, such as artificial-intelligence and machine learning, into identification and verification processes to ensure robust security and compliance. This technology-driven transformation is particularly evident in the European Union, where regulations like the GDPR and the upcoming AI Act are driving innovation while imposing strict data protection requirements.
In contrast, the United States is navigating a more fragmented landscape, with sector-specific regulations and state-level initiatives like California's Consumer Privacy Act shaping the privacy landscape. Without a unified federal privacy law, the US approach fosters rapid innovation but can create inconsistencies in privacy protections and compliance obligations.
