In the world of fraud prevention and risk management, real insight rarely comes from dashboards or reports. It comes from direct exchange between people who are solving similar problems at scale. That’s why Bureau hosted its inaugural Bureau Fraud Forum. This invite-only event brought together experts and fraud fighters from fintechs, marketplaces, and digital-first enterprises for a candid, cross-industry exchange on effective methods of tackling AI-powered fraud.

This wasn’t a vendor deck. It was a working session, grounded in real attack patterns, evasive behaviors, and system gaps. And that’s why conversations like these are critical: they help teams pressure-test their models, spot blind spots in tooling, and align on where threat vectors are headed next.

The conversation was candid, and patterns began to emerge. Here’s a breakdown of the broad consensus and where leaders believe the next wave of risk will come from.

Consensus 1: Fraud has gone from a cost center concern to a boardroom conversation

No longer viewed as just a security or compliance issue, fraud has become a full-blown business threat. Leaders spoke about three core drivers behind this shift.

First, the financial impact. Whether through chargebacks, refund abuse, or ATOs, fraud now eats directly into margins, investor trust, and operational bandwidth. Second, reputation. The cost of being perceived as vulnerable (especially in user-first digital businesses), is immeasurable and often irreversible. And third, regulation. With onboarding, KYC, and data practices now under global scrutiny, non-compliance is not just costly—it’s existential.

In short, fraud is no longer someone else’s problem. It’s everyone’s.

Consensus 2: The nature of attacks has fundamentally changed, and most defenses haven’t caught up

The transition from lone-wolf attackers to coordinated fraud rings was a recurring theme. Several participants highlighted how fraud today is often powered by syndicates who exchange toolkits, share tactics, and operate across devices, platforms, and accounts in unison.

Widely available fraud-as-a-service offerings such as jailbroken or rooted devices, proxy IPs, and virtual SIMs, allow attackers to orchestrate low-effort, high-impact fraud schemes such as simulating manipulating app behavior and bypassing weak authentication protocols, making it ridiculously easy to execute and scale up fraudulent activities with the least possible investment.

Consensus 3: Anomaly detection needs to evolve from thresholds to context

Current fraud defense systems can catch 80-85% of fraud, which often constitutes the obvious deviations from the specified thresholds. However, long-tail fraud continues to evade detection. These 15-20% of the anomalies that appear legitimate in isolation, when analyzed contextually, can reveal fraud hiding right under plain sight.

For example, an unusually high number of users operating on outdated versions of Android, such as version 9, can indicate use of emulators or manipulated environments. However, rule-based systems often ignore such anomalies, impacting overall risk-assessment. To go beyond the obvious and detect the elusive long-tail fraud, businesses need contextual intelligence that can integrate user behavior, device intelligence, and session history.

Consensus 4: AI is the new weapon -> for both sides

Generative AI and deepfakes are now a common concern, and there is a growing anxiety over their implications. As AI-driven fraud begins to move beyond document and identity fraud, security experts anticipate use of GenAI tools to democratize voice/video synthesis and KYC manipulation. 

They also anticipate deepfake-based fraud becoming mainstream, and are advocating building urgent preparedness against this emerging attack vector. To detect synthetic identities, voice spoofing, and other emerging fraud vectors, businesses can leverage AI-enabled tools including Behavioral Biometrics. It not only authenticates user identity, but also verifies how they behave across digital interactions, using patterns of typing, swiping, session flow, and device behavior. 

Consensus 5: The most effective fraud operators aren’t working alone

The core asymmetry is this: fraudsters collaborate, businesses don’t. Attackers know the entire landscape—apps, flows, incentives, loopholes. But most companies only see what happens inside their own systems.

Several leaders called for a shared threat infrastructure. It is critical that businesses collaborate and build a fraud intelligence network, say a “credit bureau of fraud” that enables them to share threat intel, unite platforms, protect user identity, and mitigate industry-wide exposure. A custom, intelligence-led SaaS platform that can capture and connect risk signals across apps, devices, and behaviors, detect patterns and hidden signals, and collectively defend against threats that are no longer siloed.

The way forward

One thing became clear at the Forum: fragmented tools and reactive workflows won’t cut it. We need unified platforms that bring together signals across onboarding, behavior, devices, and identity, and adjust trust dynamically across the lifecycle.

The Bureau Fraud Forum underscored the critical need for businesses to collaborate and build for resilience. It also highlighted the urgent need for businesses to leave behind fragmented systems and adopt unified risk decisioning platforms that can continuously monitor user behavior, reveal contextual anomalies, and dynamically adjust trust levels across the entire customer lifecycle. 

To learn how Bureau’s AI-powered infrastructure is enabling global businesses to take this leap, talk to an expert now.