How Digital Identity Helps Hospitals and Hospital Systems Prevent Identity Fraud in the Age of Agentic AI

How Digital Identity Intelligence Detects Bots, Fraud and Cybersecurity Threats

A New Era of AI-Driven Cybersecurity Threats in the Healthcare Industry 

Healthcare cybersecurity teams are facing a new kind of threat. Attackers are no longer limited to manual identity fraud attempts, simple bots or stolen credentials used one account at a time. They now use automation and AI-driven tools to test credentials, imitate user behavior and scale activity across login, account creation and transaction flows. Recent reports show that AI is making cyberattacks more scalable, more convincing and harder to distinguish from legitimate activity.

This shift changes your core challenge. It is no longer enough to validate a password, device or one-time code. Hospitals and hospital systems need to determine whether the entity behind each interaction can be trusted in that moment.

Why Digital Identity Is the New Security Perimeter for Hospitals and Hospital Systems

Many attacks begin with access that appears legitimate. Credentials are stolen through phishing or malware. Devices can be spoofed. Bots can operate slowly to avoid detection or accelerate to overwhelm systems.

Some attacks blend into normal activity. Others create unusual spikes. In both cases, individual signals can be misleading.

Digital identity intelligence helps resolve this uncertainty. It evaluates activity in context, then compares behavior against established patterns to determine whether an interaction is expected or suspicious. This approach provides a more accurate view of risk without relying on a single point of verification.

How Agentic AI Is Accelerating Sophisticated Bot Attacks

Agentic AI is changing how automated attacks are executed. Unlike basic automation, it supports adaptive behavior. Attackers can vary patterns, test defenses and move through multistep processes with less manual effort.

Bot attacks continue to grow across the digital ecosystem. Automated traffic represents a growing share of online activity, and bad bots continue to increase in volume and sophistication. According to the LexisNexis® Risk Solutions study “Evolving Threats Beneath the Surface “, automated bot attacks increased by 59% in 2025 as attackers increasingly relied on automation and more sophisticated techniques.¹

At the same time, account takeover remains a major concern. Attackers use credential stuffing and coordinated automation to compromise accounts across industries.^{1, 2}

These trends make it harder for hospitals and hospital systems to separate trusted users from malicious activity.

Why Bot Detection Requires Healthcare Digital Identity Intelligence, Not Just Activity Signals

Hospitals and hospital systems are increasingly reliant on digital channels to support patient access, engagement and self-service. Your patients expect convenient digital experiences across patient portals, online scheduling, digital registration and connected care experiences. At the same time, they have expanded the number of digital interactions that must be protected from fraud and unauthorized access.

LexisNexis Risk Solutions healthcare industry analysis identified more than 13.8 million healthcare interactions associated with confirmed fraud elsewhere in the Digital Identity Network®, highlighting the challenge of evaluating trust decisions using healthcare data alone.³

As digital engagement continues to expand, you face increasing pressure to make informed trust decisions while balancing security, patient experience and operational efficiency. Determining whether a digital interaction should be trusted has become more challenging, particularly when important context may exist beyond the visibility of your own organization.

How Shared Digital Intelligence Improves Threat Detection for Hospitals and Hospital Systems

Context becomes more powerful at scale. Attackers rarely target a single organization. They reuse tools, credentials, devices and infrastructure across multiple environments.

Shared intelligence helps you to identify patterns that extend beyond your own systems. It provides visibility into behaviors tied to known threats and helps you detect connections between accounts, devices or networks.

This broader perspective improves detection accuracy and enables faster response to emerging threats.

Balancing Cybersecurity Protection and Healthcare Patient Experience

Security measures that create unnecessary friction can drive users away. Requiring repeated authentication for every healthcare interaction often leads to abandoned registrations, logins or transactions.

At the same time, insufficient controls increase exposure for hospitals and hospital systems to identity fraud and account compromise. The goal is precision.

Using multiple identity signals allows you to identify trusted users with minimal disruption while applying additional controls only when needed.  This approach improves both security and engagement.

How LexisNexis® ThreatMetrix® for Healthcare Detects Bots, Identity Fraud and Emerging AI Attacks

ThreatMetrix® for Healthcare helps healthcare organizations detect bot activity, identity fraud and coordinated attacks by evaluating digital interactions in real time against intelligence from the Digital Identity Network. These risks often manifest as account takeover, credential abuse and impersonation attempts that appear legitimate on the surface.

The platform analyzes patterns across devices, networks and behavior to identify anomalies that signal potential risk. Automated threats often reveal themselves through activity that is inconsistent with natural human action, such as unnatural speed or repeated actions across accounts.

By connecting each interaction to broader digital intelligence, ThreatMetrix® for Healthcare helps healthcare organizations detect identity fraud earlier, apply targeted controls and stop attacks before they escalate, while allowing trusted users to move through digital experiences with minimal friction.