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First party Fraud

Overview

First-party fraud occurs when a legitimate customer (not an impersonator) abuses services e.g., lying on applications, friendly chargebacks, refund abuse, or intentional credit defaults. It blurs lines with credit risk because identity is real but intent is deceptive. Controls include application fraud scoring, income/asset verification, device/behavior analytics, and post- transaction dispute monitoring
Dispute teams coordinate with fraud ops to classify cases accurately and avoid mislabeling genuine customer issues. Regulators expect fair treatment, explainability, and clear disclosures, especially for credit decisions. Programs balance friction and prevention with step-up checks on risky behaviors, and use segmentation to distinguish error, opportunism, and organized abuse. Accurate labeling improves model training and loss forecasting.

FAQ

Why is it hard to detect?

Identity signals look legitimate. Intent cues (behavioral patterns, inconsistencies, velocity) and contextual data are needed to separate abuse from normal use.

How do chargebacks fit here?

“Friendly” chargebacks arise when customers deny valid purchases. Merchant evidence, device/IP linkage, and refund policies reduce incentives and losses.

What’s different from third-party fraud?

The customer is real; risk stems from misrepresentation or abuse. This shifts detection from identity proofing to behavioral and affordability controls.

Any compliance concerns?

Ensure fair lending, transparent decisions, and appeals. Keep clear evidence chains and policies to defend dispute outcomes to regulators and networks.

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