7 Effective Ways to Update Your Fraud Strategy for GenAI Threats

Executive Takeaways

• The Velocity Gap: Legacy static controls are failing because GenAI has reduced the cost and time of attacks to near zero, while institutional response times remain tethered to manual processes.
• From Silos to Networks: Modern fraud strategy must move from isolated “point-in-time” checks to network-level intelligence that monitors the entire customer lifecycle to prevent downstream losses.
• Operating Efficiency: Modernization is a P&L play; reducing manual review overhead and false positives directly improves margins and protects the lifetime value of legitimate customers.

Fraud teams operate in an environment that changes faster than most internal controls can keep pace with. Digital account opening has expanded access for customers, but it has also widened the attack surface for bad actors. Advances in generative AI (GenAI) are accelerating that change by reducing the cost of committing fraud and increasing its scale. What once required coordination and time can now be automated, repeated, and refined almost instantly.

Insights from a recent American Banker webinar featuring experts from Plaid and MANTL highlighted how dramatically the fraud landscape has developed. Fraud rings now operate with speed and precision that traditional controls were never designed to handle. Static rules and disconnected systems leave institutions responding after losses occur instead of stopping fraud before it causes damage.

GenAI and the Evolution of Account Opening Fraud

Digital account opening has become one of the most targeted entry points for fraud. GenAI tools allow attackers to create convincing identities with realistic documents and submit applications repeatedly to find a weakness. These tools also embolden fraud rings by making it easier to coordinate and scale attacks across numerous institutions.

Fraudsters face far fewer constraints than financial institutions. “They can test out new tools. They’re not constricted by the same legal and compliance hurdles that financial institutions have,” Tiffany Ha, Fraud Product Marketing Manager at Plaid, explained during the discussion. 

Synthetic identity fraud also continues to grow as attackers combine real and fabricated information. Because these identities often behave like legitimate customers early on, they pass initial checks and stay undetected until losses surface later.

Fraud teams can no longer depend on single-moment checks during onboarding. Effective detection calls for continuity across all sessions and interactions, not isolated decisions. Without a broader context, institutions risk approving accounts that appear acceptable in isolation but raise red flags when viewed across wider networks.

Moving Beyond Fragmented Fraud Controls

Plenty of financial institutions have assembled their fraud programs incrementally. Each new threat introduced another tool or manual review step, and these additions created fragmented environments. As a result, teams often spend more time managing systems than addressing risks as they arise.

Fraud strategy benefits from clear ownership, shared metrics, and coordination across risk, compliance, and operations. When teams operate from the same definitions and signals, they can move faster without adding friction for legitimate customers.

The webinar pointed out that modernization doesn’t mean businesses have to replace every system at once. It starts with identifying where outdated assumptions limit effectiveness. Policies designed for slower threat cycles need careful reconsideration when adversaries can probe defenses in real-time.

The Changing Role of Identity Verification and KYC

Identity verification and KYC practices are also evolving as fraud becomes more commonplace. Traditional checks focus on validating information at a single moment, but attackers exploit the gaps between institutions. A more complete view of identity behavior helps close those gaps.

Network-level intelligence adds important context. When institutions can detect patterns across devices or identities reused elsewhere, they gain early warning signs of coordinated activity.

“Someone can look very clean at account opening, but once they start interacting with your applications, transacting on your accounts, that’s where you might start to see some anomalies,” Kevin Walsh, Director of Risk and Analytics at MANTL, highlighted why this broader perspective matters.

That reality pushes fraud teams to think beyond onboarding and monitor risk throughout the customer relationship.

Technology That Supports Faster Decisions

Modern fraud teams need tools that adapt as quickly as threats tend to do. Configurable systems enable teams to adjust policies without waiting through long development cycles. Self-service controls give analysts the ability to respond as patterns change, instead of weeks too late.

Strategy for Long-Term Security

An effective fraud strategy aims to balance protection with growth. Rigid controls frustrate customers and lead to slow onboarding. Controls that are too loose invite losses and downstream risk. The right balance depends on clear data, aligned teams, and systems that are designed to adjust over time.

It’s important to treat this issue as a serious business risk, not a standalone incident. Fraud will continue to evolve as GenAI tools become more accessible, and institutions that are set up for success will focus less on individual tactics and more on building adaptable frameworks.

The Financial Impact: Reducing Manual Review and OpEx

For a CFO or Controller, the hidden cost of fraud isn’t just the direct loss from a bad actor – it’s the Manual Review Overhead required to manage a high-noise environment.

Fragmented systems and legacy rules often result in a high volume of “grey-area” flags. This forces financial institutions to scale their headcount linearly with their growth, which is unsustainable. Modernizing the fraud stack shifts the financial model in three ways:

• Decreasing the Cost per Decision: Automated, high-confidence signals reduce the need for human intervention on low-risk applications, allowing your team to focus exclusively on high-value investigations.
• Reducing “False Positive” Friction: Every legitimate customer blocked by an outdated rule represents a wasted Customer Acquisition Cost (CAC). Refining these filters ensures that over-zealous, blunt-force controls don’t claw back marketing and sales spend.
• Eliminating Technical Debt: Maintaining a “patchwork” of legacy tools often requires specialized IT resources. Consolidating into a configurable, API-driven framework reduces long-term maintenance costs and increases operational agility.

By treating fraud strategy as a component of Operational Excellence, Controllers can transform a cost center into a source of competitive advantage.