The projected 15% increase in digital ID verification checks continues the growth trend seen in the previous year, when verification checks expanded by 16%, fueled by surging e-commerce transactions.
A recent study by Juniper Research, a leading analytic authority in fintech and payment markets, forecasts that the total number of digital identity verification checks will surge to 86 billion in 2025, up from 75 billion in 2024.
According to the study, a major factor driving this rise is the widespread implementation of Strong Customer Authentication (SCA) – a regulatory framework designed to protect online transactions and reduce fraud, particularly in the fast-growing e-commerce sector.
As fraud prevention remains a top priority for merchants, Juniper Research anticipates a significant increase in the adoption of biometric identity verification methods, such as facial recognition, to improve fraud detection and customer authentication. By integrating biometric technology, merchants can adhere to SCA requirements while ensuring accurate verification of new customers and secure processing of high-value transactions.
However, taking into account the vast volume of digital transactions occurring daily, the report highlights the need for vendors to look beyond traditional security methods and adopt artificial intelligence (AI)-driven fraud detection solutions.
One key recommendation is the implementation of liveness detection, a technology that can determine whether a biometric sample — such as a facial scan — is being presented by a real, live person rather than a fraudulent copy (e.g., a photo or deepfake). AI-powered verification systems can help businesses identify emerging fraud techniques early, reducing financial losses and improving security over time.
In addition to biometric scans, behavioural biometrics is emerging as a promising solution for meeting SCA compliance while maintaining a smooth user experience. Unlike traditional authentication methods, behavioural biometric solutions don’t rely on inherent physiological characteristics (e.g. fingerprints, palm or iris scans). Instead they leverage spotted behavioural traits and patterns for identification, continuously analyzing patterns in how users interact with their devices, such as typing speed, mouse movements, and touchscreen gestures. This technique allows businesses to confirm that a user is legitimate in an automated back-end way, without requiring additional authentication steps from the customer that could slow down transactions.
Thomas Wilson, the report’s author, emphasized the rapid transformation of the digital identity verification industry. He noted that as businesses adapt to evolving regulations, they must also ensure their verification solutions provide a seamless and user-friendly experience. According to Wilson, new authentication technologies must align with advancements in consumer devices, ensuring compatibility and ease of use for a broad audience.
