How Digital Fraud is Shifting to the Mobile Layer

Financial fraud losses continue to rise year after year, despite sustained investments in awareness campaigns, regulatory controls, and detection technologies. According to the Global Anti-Scam Alliance (GASA), scammers stole over $1 trillion in 2024. While this figure represents a small fraction of total global transaction volume, its real impact is measured in eroded trust, financial harm to victims, and mounting operational and reimbursement costs for financial institutions.

What has fundamentally changed is not the existence of fraud, but where and how it succeeds.

Over the past decade, fraud has steadily shifted away from direct attacks on bank infrastructure toward the manipulation of consumers, devices and digital channels. Social engineering, authorize push payment (APP) scams, deepfake-enabled account openings, and malware-driven mobile abuse now dominate the fraud landscape. These attacks scale efficiently, adapt quickly, and often bypass traditional server-side defenses by exploiting a simpler truth: if an attacker can control the execution environment, they no longer need to breach the bank itself.

Mobile applications sit at the center of this shift. Once viewed primarily as customer experience channels, mobile apps have become a primary execution layer for financial transactions— and, increasingly, for fraud. Yet many fraud prevention strategies still treat the mobile client as a trusted blackbox, focusing detection efforts almost exclusively on backend systems and historical transaction patterns.

This growing disconnect creates a critical blind spot. As fraud becomes more automated, more distributed, and more industrialized, institutions that lack visibility into the integrity of the mobile app and device environment are left reacting to fraud after it occurs, rather than preventing it at the point of execution.

How fraud evolved—and why this moment is different

Financial fraud is not new, but digital fraud has undergone a clear evolution.

Early online fraud largely targeted backend systems, including bank servers, databases, and payment infrastructure. Over time, as these systems became better protected, attackers shifted tactics. Rather than breaking into banks, they began manipulating customers into initiating transactions themselves.

Social engineering scaled this approach dramatically. Fake ads, phishing campaigns, and impersonation schemes allowed fraudsters to bypass hardened infrastructure by exploiting human trust. While individual transactions were smaller, the attacks were easier to automate and replicate across thousands of victims.

Today, a third phase is emerging. AI-driven tooling, deepfakes, malware, and modded mobile apps allow fraud to be executed at scale with increasing sophistication. Fraud is no longer opportunistic, it is industrialized, supported by tooling, specialization, and global coordination.

Industry signals from Mobey Forum

Recent discussions among banking and payments leaders reinforce this shift. Fraud cases continue to be dominated by scams originating on social media platforms, with APP fraud cited as a particularly persistent problem. Investment scams promising unrealistic returns remain highly effective, and victims increasingly include Millennials and Gen Z , not just traditionally vulnerable populations.

A recurring challenge is underreporting. Social stigma discourages victims from coming forward, limiting institutional visibility and delaying response. As a result, awareness campaigns and education remain necessary, but insufficient on their own.

The broader takeaway is clear: fraud prevention strategies that rely solely on user vigilance and backend detection struggle to keep pace with attackers who control how transactions are initiated.

Account openings: A zero-day fraud flashpoint

Fully digital account opening has become standard across financial services. It reduces friction, accelerates growth, and improves customer experience. But it also introduces a high-value fraud opportunity at the earliest point in the customer lifecycle.

AI-generated deepfake images and videos increasingly undermine traditional KYC assumptions. While strong customer authentication and liveness checks raise the bar, attackers continue to adapt. Static controls are tested, learned, and bypassed.

The result is a difficult trade-off: automation improves efficiency for legitimate users but increases exposure when the underlying execution environment cannot be trusted. In these cases, automation itself becomes a liability.

Detection remains essential, but incomplete

Financial institutions have invested heavily in centralized fraud detection systems, including SIEMs, anti-fraud engines, and issuer-side analytics. These systems are critical — but they are inherently reactive and often siloed.

Most detection efforts focus on the issuing side of the transactions, while the signals from the receiving side and the client environment remain underutilized. Fraudsters exploit this asymmetry, adjusting transaction size, frequency, and timing to remain below detection thresholds or shift activity across institutions.

As fraud tactics evolve continuously, detection alone becomes a moving target. One that is difficult to win without earlier, higher-fidelity signals.

Fraud at scale: Crime as a Service (CaaS)

Another accelerant is the rise of fraud-as-a-service. What was once the domain of individual actors has become a specialized ecosystem. Malware, scripts, phishing kits, and operational playbooks are readily available through underground marketplaces.

This lowers the barrier to entry and shortens the learning curve for attackers. Fraud capabilities that once required deep expertise are now commoditized, enabling rapid experimentation and iteration at scale.

Regulation is slowly catching up

Legislation continues to evolve in response to these challenges. Mandatory fraud reporting and emerging liability-sharing models aim to improve accountability and incentivize better controls. However, fraud does not respect national borders, and regulatory coordination often lags behind attacker innovation.

While policy plays an important role, defenders remain constrained by legal frameworks and compliance obligations — constraints that attackers simply ignore.

Why mobile apps sit at the center of modern fraud

Most modern fraud scenarios now intersect with a mobile application at a critical moment: account opening, authentication, or transaction initiation. Even when fraud originates on social media or through phishing, execution almost always happens inside a mobile app.

This matters because mobile apps operate in untrusted environments. They run on devices that financial institutions do not own or control. Attackers exploit this reality through malware, runtime manipulation, repackaging, and automated abuse — techniques that invalidate many server-side trust assumptions.

Critically, these attacks do not require a backend breach. A legitimate, fully patched app can still be abused if its execution environment is compromised. Treating the mobile client as inherently trustworthy creates a structural gap that attackers increasingly exploit.

Common mobile-driven fraud patterns observed in the wild

Several mobile-centric fraud patterns recur across industries:

Malware-assisted fraud

Malicious utility apps or repackaged versions of trusted apps intercept credentials, manipulate transactions, or initiate fraudulent activity without user awareness.

Tampered onboarding and KYC flows

Attackers manipulate camera inputs, SDK interactions, or execution environments to bypass automated identity checks during account opening.

Modded apps and scripted automation

Repackaged apps combined with bots abuse APIs, probe fraud thresholds, or automate low-and-slow attacks designed to evade detection.

What these patterns share is a reliance on client-side manipulation — activity that is largely invisible to backend fraud systems until damage has already occurred.

How mobile app security changes the fraud equation

Mobile app security does not replace existing fraud detection systems — but it strengthens them by addressing what backend controls cannot see.

App hardening increases the cost and complexity of reverse engineering and runtime tampering. Runtime protections detect abnormal execution conditions that strongly correlate with fraud, such as debugging, hooking, or malicious code injection.

Equally important, mobile apps generate real-time trust signals about the app and device environment. When integrated into fraud intelligence platforms, these signals enable earlier risk assessment and more precise intervention.

App attestation extends this capability further by allowing institutions to verify, at runtime, whether API requests originate from a genuine, untampered app running on a trustworthy device — without requiring app rebuilds or redeployment.

Treat mobile apps as active fraud control points

As fraud shifts toward the consumer and mobile layer, the limits of backend-only defense models become increasingly clear. Detection remains necessary, but prevention requires visibility earlier in the transaction lifecycle, where intent is formed and execution begins.

Mobile applications are no longer passive delivery channels. They are enforcement points, signal generators, and control surfaces in the fight against fraud. Institutions that integrate mobile app integrity and device trust into their fraud strategies gain earlier detection, stronger prevention, and reduced reliance on blunt, customer-disruptive controls.

Fraud is ultimately a trust problem. Solving it requires extending trust decisions beyond backend systems to include the mobile apps that initiate transactions in the first place.

To learn more about how we can help you with comprehensive security for your mobile apps, contact a Guardsquare expert today.