Service · Fraud Risk Review

Fraud Risk Assessment for Digital Platforms & AI Systems

Identify fraud vulnerabilities before attackers do. A structured assessment that maps your platform's fraud attack surface, detects signal gaps, and surfaces hidden risk across identity, behaviour, and transaction layers.

Most Platforms Discover Fraud Risk After the Loss

Weak onboarding controls, exploitable payment flows, and automated abuse patterns often remain hidden until fraud networks scale. By then, the cost is real.

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Invisible Attack Surfaces

Fraud vectors are only visible from an attacker's perspective. Internal teams see the product — not the exploitation path.

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Signal Gaps in Detection

Most detection systems monitor for known fraud patterns. Novel vectors and coordinated attacks bypass rules designed for yesterday's fraud.

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AI Agent Blind Spots

Platforms deploying autonomous agents are introducing new fraud surfaces that traditional monitoring systems were not designed to cover.

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Late Detection Costs More

Fraud rings move fast. Every cycle without detection is additional loss, and network effects compound the damage quickly.

What the Assessment Covers

A structured review across all five fraud intelligence layers, tailored to your platform's specific architecture and risk profile.

1
Platform Fraud Attack Surface Mapping Identify all exploitation paths across onboarding, transactions, referrals, and platform-specific flows.
2
Fraud Signal Gap Analysis Benchmark current monitoring coverage against the Zarelva Fraud Signal Library. Identify what you're missing.
3
Behavioural Anomaly Detection Review Assess whether current systems can identify non-human patterns, velocity anomalies, and coordination signals.
4
Identity & Device Risk Analysis Review onboarding controls for synthetic identity vectors, device reuse patterns, and account farming signals.
5
AI Agent Abuse Risk Assessment For platforms with AI agent deployments — evaluate agent identity, delegation chains, and behavioural monitoring gaps.
6
Fraud Scenario Simulation Model specific fraud attack scenarios against your platform architecture to assess detection confidence.

Assessment Deliverables

Every engagement produces a structured set of outputs that your team can act on immediately.

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Platform Fraud Exposure Map

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Fraud Signal Gap Analysis

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Attack Scenario Report

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Financial Risk Impact Estimate

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Fraud Prevention Strategy

Built for High-Risk Digital Environments

Fraud risk assessments are most valuable where fraud losses are high, fraud patterns are evolving rapidly, or new product surfaces have outpaced detection systems.

🏦 Fintech companies
🛒 Digital marketplaces
🤖 AI startups deploying agents
💳 Payment platforms
📱 SaaS platforms with financial flows
🏢 Digital lending platforms
🌐 Cross-border platforms

Why Zarelva

Zarelva is an independent fraud intelligence consultancy with investigative and detection architecture experience across Flipkart, Google, Amazon AWS, and G2 Risk Solutions. No vendor affiliations, no platform bias — just structured fraud intelligence applied to your specific environment.

Zarelva publishes open research on fraud signals and AI agent fraud detection, including the Fraud Signal Library and Agent Risk Engine — tools built to support the same assessment methodology used in client engagements.

Request a Fraud Risk Assessment

Engagements are scoped to your platform. A brief 30-minute discussion is enough to outline the assessment approach and identify the highest-priority risk areas.

hello@zarelva.com →

Independent advisory. No vendor affiliations. Engagements accepted for serious, well-documented fraud risk matters.