## Product overview

First-party fraud (FPF) occurs when an individual uses their **own real identity** to open accounts, access credit, or transact—then commits a dishonest act such as:

- Disputing legitimate transactions (chargeback abuse)
- Defaulting on loans or payments
- Exploiting refund or return policies
- Securing funds with no intent to repay

Unlike third-party or synthetic fraud, there are no stolen credentials or fake identities. This makes FPF **uniquely hard to detect** with traditional fraud tools. The cost is enormous: U.S. businesses face **$100B+ in annual losses**, with financial services, fintechs, BNPL, telcos, gaming, and e-commerce among the hardest hit.

## Industries it fits

- **Financial services**: Detect repeat fraudsters at account opening or during payments
- **Lending & BNPL**: Spot borrowers likely to commit chargeback abuse or defaults
- **Gaming**: Prevent duplicate accounts and fraudulent sign-ups
- **Government & benefits**: Block multiple claims tied to the same identity
- **E-commerce & subscriptions**: Flag consumers with dispute-heavy histories before renewals
- **Payments & wallets**: Protect against fraudulent ACH, card, P2P, and wire transactions

## Business and operational outcomes

### 1. For compliance and risk teams

- Reduce fraud losses tied to chargebacks, disputes, and defaults
- Identify high-risk applicants with prior confirmed fraudulent activity
- Detailed reason codes support transparent decisioning and audits
- Coverage expansion through consortium contributions

### 2. For growth and onboarding teams

- **Safer onboarding**: Catch high-risk applicants before they enter your ecosystem
- **Protect portfolio health**: Block consumers with histories of payment abuse
- **Configurable thresholds**: Tune risk signals and fraud scores to align with risk appetite
- **Support for multiple flows**: From new applications to mid-journey payment verification

### 3. For support and operations

- **Fewer escalations**: Reduce dispute handling by blocking known abusers upfront
- **Clear decision signals**: Agents see risk signals, reason codes, and fraud scores
- **Operational efficiency**: Automated fraud checks reduce manual reviews

## Performance considerations

- **Latency:** Typical response time for RiskOS™ API is under 500ms per call.

- **Accuracy:** At 10% risk population, Sigma FPF captures >50% of FPF with high precision; at 3% risk depth, it can flag 30%+ of true first-party fraud.

- **Scalability:** Supports enterprise volume and big data workloads.

## **Known Limitations**

- Primary coverage is US; international signals are planned but not yet fully supported
- Not a consumer reporting agency: cannot be used for FCRA-regulated adverse action
- Dependent on ongoing, high-quality consortium data contributions for optimal performance.
- Rate limits and provisioning controls apply for very high-volume or bulk/batch use cases

Updated 3 months ago