Embedding Security: Designing Fraud Risk Out of Business Transactions

Embedded payments are becoming a core feature of modern business platforms, weaving transactions directly into everyday operational workflows. As payments shift, however, fraud risk shifts with them. In embedded environments, threats can no longer be managed effectively through point solutions that activate only after a transaction is already in motion.

Instead, fraud prevention must move upstream. In embedded finance, security becomes a matter of smarter payment design rather than reactive intervention. By embedding coordinated controls throughout the payment workflow, from identity and access to authorization and execution, organizations can reduce exposure earlier, strengthen resilience and build security directly into transactions before funds ever move.

Embedded Finance Delivers Value—and New Risk

Why Legacy Fraud Prevention Breaks in Embedded Finance

Designing Fraud Out: How Embedded Payments Can Reduce Risk Upfront

Build Fraud Resilience Into the Payment Layer

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Embedded Finance Delivers Value and New Risk

Embedded payments are accelerating business efficiency and control, but they are also broadening the fraud surface, often faster than organizations’ risk infrastructure can adapt.

Embedded finance has moved into the mainstream.

WEX identifies embedded finance as one of the top business payment trends shaping 2026, with transaction value projected to exceed $7 trillion, nearly tripling from $2.6 trillion in 2021. By embedding payments directly into nonfinancial platforms, businesses can deliver seamless, “invisible” payment experiences while gaining greater operational efficiency and competitive advantage.

Adoption data confirms the benefits. According to Mastercard, nearly three-quarters of embedded finance users report improved cash-flow visibility, while more than three-quarters cite cost savings and increased working capital flexibility. Embedded payments are no longer experimental; they are becoming foundational infrastructure for modern business platforms.

2x-3x

One estimate of the increased rate at which fraud attempts are targeting embedded finance compared to traditional banking channels

Embedded payments’ growth is widening the fraud attack surface.

That same integration, however, is fundamentally changing where fraud risk lives. Industry research notes that as payments become platform-based and driven by application programming interfaces (APIs), risk is no longer confined to a single channel or transaction type. Instead, it increasingly spans software layers, third-party partners and workflows.

Moreover, as noted by WEX’s President of Corporate Payments, Eric Frankovic, attack surfaces are expanding at the same time that threat actors themselves are becoming more sophisticated. One industry analyst estimates that fraud attempts targeting embedded finance products are growing two to three times faster than those seen across traditional banking channels—an indication that risk is accelerating alongside adoption.

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Why Legacy Fraud Prevention Breaks in Embedded Finance

Fraud strategies built for traditional banking struggle in embedded payment environments, where risk is distributed across platforms, transactions move at machine speed, and legacy detection tools lack the adaptability to keep pace.

35%

of organizations have delayed embedded finance and banking-as-a-service initiatives due to fraud concerns.

Embedded finance disperses risk across multiple owners.

As research points out, fraud risk in embedded finance models no longer resides within a single institution or channel. When financial services are delivered through third-party platforms and vertical software, responsibility for security, onboarding and transaction integrity is distributed across sponsor banks, FinTech intermediaries, developers and end platforms.

Gulf Business reports that as APIs extend financial capabilities into nonfinancial environments, banks and payment providers often cede direct control over how those interfaces are accessed, secured and monitored, increasing exposure to misuse or abuse. This means that threats often emerge at the “seams” between systems—where visibility is obscured and accountability is fragmented. For example, a recent data breach reported by CNN at real-estate loan and mortgage company SitusAMC could have impacted major banks such as JPMorgan Chase and Citi, leaving their data vulnerable to theft. The cyberattack highlights how even one insecure touchpoint can jeopardize an entire ecosystem.

This vulnerability helps explain why Alloy finds that 35% of organizations have delayed embedded finance and banking-as-a-service initiatives due to fraud concerns, despite strong business demand.

Instant payments and APIs compress fraud detection windows.

Embedded payment models are designed for speed and convenience, but that same efficiency sharply reduces the time available to identify and stop fraud. Instant approvals, one-click transactions and API-driven execution shrink detection windows from hours or days to seconds, leaving little room for manual intervention once a transaction is initiated.

Trustpair observes that as faster payment rails proliferate, funds can be transferred, withdrawn or laundered before fraud teams even detect anomalous activity, amplifying the impact of any single failure point.

Rule-based and reactive fraud models cannot keep pace.

Traditional fraud prevention tools were built for a slower, more centralized banking environment. Research published in Premier Science notes that many institutions still rely on static, rule-based systems that flag transactions based on fixed thresholds or known risk indicators. While transparent and easy to implement, these models are fundamentally reactive and struggle to adapt as fraud tactics evolve.

Rule-based systems also generate high false-positive rates, disrupting legitimate transactions and increasing operational overhead through manual reviews that do not scale to modern transaction volumes. In embedded finance environments, where transaction velocity is high and risk signals are distributed across platforms, these limitations become structural weaknesses rather than operational inefficiencies.

Alloy notes that attempts to apply one-size-fits-all fraud controls across diverse embedded partnerships can further exacerbate friction, creating bottlenecks without meaningfully reducing exposure. In addition, Trustpair warns that as fraud grows more AI-driven, automated and adaptive, static detection tools will increasingly lag behind the threats they are meant to contain.

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Designing Fraud Out: How Embedded Payments Can Reduce Risk Upfront

Embedded payments enable a proactive approach to fraud by layering coordinated defenses directly into payment workflows, delivering control and visibility before funds move.

Payment design is becoming the first line of defense.

A different model is emerging, one that treats fraud prevention as an architectural discipline. WEX emphasizes that fraud risk is reduced most effectively when multiple, coordinated defenses are embedded throughout the payment workflow. These include artificial intelligence (AI)-based automation, virtual cards with configurable limits, role-based permissions, multifactor authentication, real-time transaction monitoring and stronger identity verification.

Layered across identity, authorization and execution, these controls provide visibility and enforcement before transactions occur, reducing reliance on downstream intervention.

24%

of banking CEOs say enhanced cybersecurity is the top benefit of using AI—more than any other factor.

Layered defenses translate design into operational control.

Virtual cards exemplify the shift from reactive monitoring to design-led control. Built-in constraints such as spend limits, merchant restrictions and dynamic authorization align payment capability with operational intent, reducing exposure by default. Partnerships like the collaboration between WEX and Nuvei show how these instruments can be embedded directly into merchant ecosystems, reducing risk without relying on downstream intervention.

AI-driven automation reinforces this layered approach. KPMG finds that 70% of banking CEOs plan to allocate 10% to 20% of their budgets to AI in the coming year, with fraud detection and cybersecurity cited as the most immediate sources of value. At 24%, enhanced cybersecurity ranks as the most commonly reported benefit of AI adoption, underscoring the efficacy of prevention embedded directly into payment workflows.

Embedded fraud prevention is driving confidence for business leaders.

Mastercard research finds that 74% of users credit embedded finance with significantly reducing fraud risk, illustrating how controls embedded into workflows can outperform standalone monitoring tools.

These protections will only become more indispensable. Trustpair emphasizes that as threats get more sophisticated, prevention tactics are shifting away from siloed defenses toward a model built on shared insights, system compatibility and coordinated enforcement across platforms.

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Build Fraud Resilience Into the Payment Layer

Embedded payment models create an opportunity to move fraud prevention upstream—into the design of how payments are initiated and executed. Organizations that treat payments as infrastructure rather than endpoints can design fraud risk out of everyday transactions.

PYMNTS Intelligence recommends the following strategies for upstream fraud control:

Anchor fraud controls at identity and access. Enforce strong identity verification, role-based permissions and multifactor authentication at onboarding and before payment initiation.

Constrain risk by default. Use configurable instruments such as virtual cards, spend limits, merchant controls and dynamic authorization rules to align payment capabilities with operational intent.

Integrate intelligence directly into workflows. Deploy AI-driven monitoring and decisioning at key workflow stages to surface anomalies in real time, not after execution.

Centralize visibility across platforms. Establish unified views of users, permissions, transactions and integrations to close gaps at system handoffs.

Automate enforcement, not just detection. Embed controls that can block, reroute or step up authentication automatically when risk thresholds are met.

By layering defenses into the payment flow itself, organizations shift from reactive monitoring to proactive enforcement. Security becomes a part of how work gets done, enabling embedded payments to scale with confidence—even as fraud tactics evolve.

The era of reactive fraud prevention is over. Legacy models simply cannot keep pace with the speed of instant payments and APIs. We are moving toward a future where security isn’t an afterthought but a core component of payment design—effectively designing fraud risk out of the transaction before it ever begins.”

Eric Frankovic
President of Corporate Payments, WEX