How to Stop Identity Fraud Before It Starts: Building Trust in a Synthetic World

Patrick Harding, Chief Product Architect at Ping Identity, explains how companies can prevent identity fraud before it occurs. This article originally appeared in Insight Jam, an enterprise IT community that enables human conversation on AI.

As artificial intelligence (AI) rapidly evolves, so too does the threat landscape. Deepfakes and AI-generated impersonations have become mainstream attack tools for bad actors. Attackers can now mimic voices, faces, and behaviors to impersonate CEOs, CFOs, employees, and even consumers. These fake personas are often deployed across emails, video calls, and voice messages, making it increasingly difficult for recipients to distinguish what is real from what is fake.

At the same time, we’re entering the age of agentic AI, in which autonomous AI agents are capable of acting on behalf of humans or organizations. While these systems have enormous potential to improve efficiency and responsiveness, they also expand the attack surface. Malicious actors can now deceive these machines with lookalike sources, or even deploy rogue AI agents to interact convincingly with humans and other systems, exploiting trust in automated workflows.

From cloned executive voices authorizing fraudulent wire transfers to synthetic videos gaining access to secure systems, identity fraud is now more sophisticated and difficult to detect than ever before. This is taking a large toll on public trust, with 75 percent of consumers expressing more concern about personal data security than five years ago. To defend against identity fraud in an AI-powered world, organizations must shift from a reactive to a proactive approach. That begins with accepting a hard truth: traditional security measures were never designed to detect synthetic identities or prevent these attacks. If we want to stop AI-driven identity fraud before it starts, we need to build trust into the fabric of our digital interactions, starting now.

Embracing a Proactive, Identity-First Defense

In a world where bad actors can convincingly impersonate someone’s voice or face, passive defenses and static credentials are no longer enough. Without a strong, multifaceted security posture, organizations risk not only falling victim to an attack but also failing to detect it until after the damage is done. That’s why it’s critical to take proactive measures now, before threats materialize.

Here’s how to get there:

1. Tighten privileged access. 

Dormant accounts, excessive permissions, or outdated access methods pose unnecessary risks to organizations. Begin reviewing and cleaning up privileged access by deactivating unused accounts, revoking temporary access as appropriate, and replacing weak credentials and authentication processes with more secure alternatives like biometrics or cryptographic passkeys. From there, regularly audit who has access to what and why. A simple rule to guide the process: only grant access to those who truly need it.

2. Adopt real-time risk detection and identity verification. 

Identity verification and risk detection can no longer be static. Real-time risk detection, powered by machine learning, can analyze login behavior and other data to spot unusual patterns before a breach occurs, and dynamically adjust access controls accordingly.

Set up alerts for logins at unusual hours, from unfamiliar locations, or on unfamiliar networks, and ensure someone is available to respond when those red flags appear. Liveness detection and behavioral biometrics are particularly valuable in high-risk scenarios, such as onboarding or authorizing major transactions.

3. Strengthen MFA. 

If multi-factor authentication (MFA) isn’t already deployed universally, make it a top priority, especially for sensitive systems and user groups. Start by adopting phishing-resistant authentication approaches like mobile push approvals and QR codes to help better protect against credential-based attacks. Also consider leveraging verifiable credentials that allow users to prove who they are without oversharing personal information. With these proactive steps in place, organizations can reduce vulnerabilities before they’re exploited.

Building for Long-Term Trust

While some of these proactive, immediate controls can block many AI-driven threats before they escalate, true, long-term resilience requires deeper architectural shifts. This includes embracing decentralized and verified identity.

Traditional identity verification models often rely on central identity stores. But as attackers increasingly target these valuable repositories of information, it’s clear that a more distributed approach is needed. Decentralized identity models shift control into the hands of users, allowing them to hold and selectively share credentials issued by trusted sources. This limits the amount of sensitive data stored in vulnerable locations, reduces the risk of mass breaches, and strengthens individual ownership of digital identity.

At the same time, passwordless authentication must become the new norm. Passwords remain one of the easiest entry points for bad actors and one of the most frustrating parts of the user experience. Replacing them with passwordless authentication, including passkeys and biometrics, improves protection while also making digital experiences smoother and more intuitive for users.

Zero-trust architecture is also essential in this new reality. Trust is no longer something that can be granted once and assumed indefinitely. Every interaction, regardless of network location, user role, AI agent, or past behavior, should be continuously verified. This model is especially critical as attackers become more adept at mimicking internal users and hijacking legitimate access paths.

Trust Is the Ultimate Target

At the end of the day, the greatest casualty of AI-powered identity fraud is trust in digital channels. That loss of trust could have devastating ripple effects across sectors like banking, healthcare, government, and beyond. But there is a way forward.

Ultimately, identity verification systems must evolve to be more intelligent and agile because static rules and processes are no match for fast-moving threats. Verification processes must be adaptive, decentralized, and capable of interpreting contextual signals, such as device posture, user behavior, and geolocation, to make smarter and more secure access decisions. It’s this layered, intelligent approach that strengthens defenses and restores trust in digital systems now, as well as against the synthetic threats of the future.