How to build fraud defenses that withstand the AI Era: A guide for executive leaders navigating modern identity risk

The fraud landscape 

Generative AI has significantly lowered the technical barrier for committing fraud, making it alarmingly accessible to novices while also empowering organized criminal networks to exploit human and digital vulnerabilities with unprecedented speed and sophistication. The rise of Fraud-as-a-Service tools, kits, and support offerings further amplifies the threat.  

For business leaders navigating identity-related risks, the challenge often feels like a game of whack-a-mole: as soon as one threat is neutralized, another pops up. Aging, siloed fraud defenses can't keep pace. So how do you respond? 

This guide outlines key elements of a layered, modern fraud strategy that protects every phase of the identity journey—from onboarding and authentication to high-risk actions and account recovery. Think of it as a guidepost on the road to a more resilient and trusted identity defense framework. Should you wish to dive deeper, set up a discovery session with a Mitek expert.

Fortify document verification with AI, biometrics, and trusted data sources 

According to 404 media, the approximate cost of a quality fake ID is now just $15. Document verification remains a cornerstone of identity proofing, but best-in-class solutions must go beyond simple image capture. Using advanced machine learning and computer vision to detect forged, altered, or signs of synthetic documents is imperative.  

Cross-checking PII such as name, SSN, and address against trusted data sources adds another layer of risk mitigation. When integrated into an adaptive, risk-based workflow, these capabilities enable businesses to verify legitimate users quickly and confidently while filtering out common fraud.  

Layering signals increases verification accuracy 

Document verification is an essential part of identity proofing, but it can’t stand alone. Modern fraud detection relies on combining and orchestrating signals across systems. For example, adding biometric face matching and face liveness detection ensures that the person presenting the ID is both real and present. 

Additional identity signals may include: 

• Document liveness 
• Proof of address 
• Digital footprint analysis 
• Geolocation 
• Payment card checks 
• Email reputation 
• PEPs and sanctions checks 

A dynamic orchestration layer pulls these signals together, adjusting friction in real-time based on threat signals. For example, a low-risk returning customer may flow through seamlessly, while a high-risk password reset request from a suspicious device could trigger biometric re-verification. 

Fight Gen AI-fueled fraud tactics with AI-powered defenses 

According to The Financial Brand, professional criminals and fraud rings are now identified as the culprits in 71% of fraud incidents.  

Generative AI is supercharging fraud operations with three sophisticated tactics increasingly used in combination: template attacks, deepfakes, and injection attacks. 

1. Template Attacks 

Criminals exploit the known layouts of official ID documents—like passports or driver’s licenses—to create convincing digital forgeries. These fakes replicate design elements such as fonts, layouts, data formats, and visual security features to convincingly mimic authentic documents. Enhance AI document verification systems with capabilities to quickly detect patterns indicative of coordinated fraud rings. 

Mitigation includes: 

• Detecting repeat image use (face velocity) 
• Identifying reused layouts or document backgrounds 
• Maintaining a library of known fraudsters

2. Deepfakes 

Deepfake technology enables fraudsters to create AI-generated images or videos that impersonate real users. 

Mitigation includes: 

• Detecting digital manipulation 
• Spotting AI-generated inconsistencies (e.g., lighting, symmetry) 
• Comparing biometric data across channels for inconsistencies 

It's essential to choose a solution that analyzes various layers of images or videos to identify left-behind artifacts indicative of deepfake generation, including complex or less common types. 

3. Injection Attacks 

Attackers insert pre-recorded or synthetic media into biometric verification flows, often via virtual cameras, to bypass liveness detection. 

Mitigation includes: 

• Detecting virtual camera use 
• Spotting suspicious resolutions or frame duplication 
• Comparing capture data with server-side evidence for tampering 

Instead of relying solely on software to analyze image content, strengthen your defenses by also monitoring the transmission channel or “stream” from which the media originates. 

Remember, fraudsters combine advanced tactics so it is critical that your defenses are complete.  

Strengthen Identity assurance throughout the customer lifecycle 

Fraud prevention doesn’t stop at onboarding. Criminals often bide their time, waiting until accounts are established before striking. In other cases they focus on weak links like passwords to gain unauthorized access, steal money, and takeover accounts. 

A modern approach secures the entire identity lifecycle, not just the pint of entry: 

This full-lifecycle approach is critical in defending against omnichannel attacks.

Don’t overlook physical channels 

As organizations invest heavily in securing digital identity flows, fraudsters increasingly shift their focus to physical locations such as bank branches and retail stores, where defenses are often weak or inconsistent. These environments have become a significant vulnerability in the identity lifecycle. Criminals present high-quality forged IDs and use social engineering tactics to manipulate frontline staff who often lack the tools or training to verify identities accurately in real time.  

To close this gap: 

• Deploy real-time, automated document and biometric checks in branches and retail stores 
• Train staff on new fraud tactics and digital tools 
• Adopt an adaptive, risk-based approach that helps strike the right balance between preventing fraud and optimizing the customer experience 

Applying the same layered verification logic used in digital processes to in-person interactions ensures every identity interaction—regardless of where it occurs—is protected. 

Rethink authentication and recovery—Passwords aren’t enough 

Phishing, SIM swaps, and social engineering have rendered passwords and even some MFA methods ineffective. Attackers exploit weak authentication and outdated recovery processes to take over accounts, change personal information, move funds, and make purchases. 

Biometric authentication strengthens security, but not all approaches are equal. Unlike device-based methods that can be bypassed by entering a PIN, cloud-based biometrics: 

• Confirm the person—not just the device 
• Enable a true independent authentication factor 
• Provide consistent security across channels and devices 
• Resist spoofing with advanced liveness and GenAI attack detection 
• Make recovery faster for real customers and harder for fraudsters to exploit. 

Enrolling biometrics early in the customer lifecycle, ideally during onboarding, facilitated trusted low-friction authentication and secure account recovery. Modernizing both authentication and recovery is essential to closing two of the most targeted gaps in the identity lifecycle. By implementing cloud-based biometric solutions, organizations can streamline user experiences while mitigating risks associated with account takeovers and unauthorized access. 

Use “good friction” as a trust signal 

When applied selectively and intelligently, friction can strengthen trust without derailing the customer experience. In high-stakes moments users are often willing to tolerate a little extra verification if it feels purposeful and smooth.  

Good friction principles: 

• Apply friction as justified by risk: Dynamic flows should allow low-risk users to move quickly through security while triggering extra checks for anomalies or high-risk behaviors. 
• Employ fast, intuitive security: Think biometric face scans with passive liveness detection over passwords, or automated ID capture over manual form-filling. 
• Reinforce user confidence: Clear messaging, accessibility features, and seamless design reduce frustration and show customers that you’re protecting them without making them jump through unnecessary hoops. 

When executed well, good friction can increase trust and drive higher acquisition.

Building a modern Identity Verification stack  

In the age of AI-driven fraud, a modern solution must go beyond point-in-time checks. It needs to verify identity accurately at onboarding, authenticate users seamlessly during engagement, and enable smart re-verification when risk signals spike — all while staying a step ahead of evolving threats like deepfakes, synthetic identities, and injection attacks. 

Key capabilities include: 

• AI-resilient identity verification that detects generated forgeries, deepfakes, face morphs, template attacks, and fake biometrics 
• On-demand re-verification that’s fast, user-friendly, and ready when needed 
• An intelligence layer that continuously learns from new threats and signals across channels

Together, these layers form a dynamic defense system that adapts as fast as fraud evolves. 

Conclusion: It’s time to modernize 

Generative AI and automation have changed the game for fraud and the way we defend against it. As tactics grow more sophisticated and collaborative, businesses must respond with strategies that are equally dynamic. 

To protect your business and customers: 

• Verify identity with multi-layered AI-powered defenses that stand up to AI-fueled threats 
• Secure every stage of the identity journey 
• Don’t let physical channels be a weak link in your security 
• Replace dated authentication methods and improve the customer experience with real-time, biometric-based trust and advanced fraud detection capabilities  

Fraudsters are layering their tactics. Your defenses must do the same. 

Building or evaluating your identity verification stack?

Download the IDV Buyer’s Guide

Designed for product owners, this guide helps you navigate the complex IDV marketplace by aligning your business requirements, risk tolerances, and customer expectations. Learn how to ask the right questions and select solutions that support both user experience and security goals. 

About Kim Martin - VP Global Growth Marketing at Mitek

Kim Martin is the Vice President of Growth Marketing at Mitek Systems, where she leads global initiatives across field marketing, content, digital marketing, and demand generation. She brings deep expertise in identity verification and biometrics from her previous role at ID R&D, a Mitek company, where she oversaw global marketing. Kim has held leadership roles at multiple technology companies, including being a founding member of a global marketing advisory firm.