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Introducing Composer: Fraud and Payment Orchestration on One Canvas

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The unified orchestration layer for wallets and alternative payments

Vault

The secure repository for all your payment methods

Optimize

Workflow-driven payments intelligence for smarter routing and higher auth rates

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A flexible fraud and authentication layer. Instantly add advanced fraud tools and 3DS

Agentic

One integration to sell inside ChatGPT, Gemini, and every agentic platform

Composer

The visual workflow builder that ties fraud, identity, and payment routing together in one place

View How Spreedly

Connects to your favorite payment methods
Optimizes your revenue
Protects your data
Reduces fraud
View the Demo
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Connect

The unified orchestration layer for wallets and alternative payments

Vault

The secure repository for all your payment methods

Optimize

Workflow-driven payments intelligence for smarter routing and higher auth rates

Protect

A flexible fraud and authentication layer. Instantly add advanced fraud tools and 3DS

Agentic

One integration to sell inside ChatGPT, Gemini, and every agentic platform

Composer

The visual workflow builder that ties fraud, identity, and payment routing together in one place

View How Spreedly

Connects to your favorite payment methods
Optimizes your revenue
Protects your data
Reduces fraud
View the Demo
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The State of Checkout 2026
The Tokenization Decision Guide
Own the Tokens, Own the Agentic Commerce Customer

Introducing Composer: Fraud and Payment Orchestration on One Canvas

Read More
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Connect

The unified orchestration layer for wallets and alternative payments

Vault

The secure repository for all your payment methods

Optimize

Workflow-driven payments intelligence for smarter routing and higher auth rates

Protect

A flexible fraud and authentication layer. Instantly add advanced fraud tools and 3DS

Agentic

One integration to sell inside ChatGPT, Gemini, and every agentic platform

Composer

The visual workflow builder that ties fraud, identity, and payment routing together in one place

View How Spreedly

Connects to your favorite payment methods
Optimizes your revenue
Protects your data
Reduces fraud
View the Demo
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Take a look at all of our resources and get the information you need to grow your business

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Featured resources

The State of Checkout 2026
The Tokenization Decision Guide
Own the Tokens, Own the Agentic Commerce Customer

Introducing Composer: Fraud and Payment Orchestration on One Canvas

Read More
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Payment Token Ownership & Portability
Intelligent Payment Optimization
Fraud Prevention & Authentication
Operational Agility & Simplicity
Centralized Management & Reporting

Platform Pillars

Connect

The unified orchestration layer for wallets and alternative payments

Vault

The secure repository for all your payment methods

Optimize

Workflow-driven payments intelligence for smarter routing and higher auth rates

Protect

A flexible fraud and authentication layer. Instantly add advanced fraud tools and 3DS

Agentic

One integration to sell inside ChatGPT, Gemini, and every agentic platform

Composer

The visual workflow builder that ties fraud, identity, and payment routing together in one place

View How Spreedly

Connects to your favorite payment methods
Optimizes your revenue
Protects your data
Reduces fraud
View the Demo
Glossary
November 5, 2026

False Positive (fraud context)

A false positive in payments fraud detection is a legitimate transaction that has been incorrectly identified as fraudulent, triggering a decline, a hold, or a manual review that the customer experiences as a failed payment. The cardholder was genuine, the transaction was authorized by the actual card owner, and the payment should have been approved, but the fraud detection system incorrectly classified it as suspicious.

False positives are the invisible cost of fraud prevention. The more aggressive a fraud prevention system's thresholds, the more fraud it catches, but also the more legitimate transactions it incorrectly blocks. A merchant that sets fraud scoring thresholds very low will decline very little fraud but also decline very few legitimate customers. A merchant that sets thresholds very high will decline essentially no legitimate customers but will also let through a lot of fraud. The optimal threshold minimizes the combined cost of fraud losses and false positive losses.

False positives are commercially costly in two dimensions. The immediate cost is the lost sale, a declined legitimate customer is revenue that does not happen. The longer-term cost is customer relationship damage: a cardholder who experiences an unexpected payment decline, particularly without clear explanation, may lose trust in the merchant, contact their bank to dispute the "failed" transaction, or simply not return. Research by Javelin Strategy & Research found that the revenue lost to false payment declines significantly exceeds the revenue lost to actual fraud in many e-commerce categories.

Reducing false positives without increasing fraud requires more sophisticated fraud tools, better signal quality, more contextual data, and Machine Learning Fraud Detection that distinguishes borderline legitimate transactions from borderline fraudulent ones. Risk-Based Authentication (RBA) is specifically designed to apply additional friction (rather than an outright decline) to borderline transactions, giving legitimate cardholders a path to complete their purchase while still providing protection.

Frequently Asked Questions

How can merchants measure their false positive rate?

Direct false positive measurement requires following up on declined transactions to determine how many were legitimate. This can be done by surveying declined customers, analyzing re-attempt patterns (legitimate cardholders often try again on the same card shortly after a decline), or reviewing declined transactions that were successfully completed in a subsequent session with identical cardholder data. Some fraud vendors provide estimated false positive rates based on industry benchmarks and the merchant's specific threshold configuration.

What is the difference between a false positive and a soft decline?

A false positive is a classification error in a merchant's or fraud tool's assessment, a legitimate transaction incorrectly flagged as fraudulent. A Soft Decline is a specific response from the issuing bank indicating that the transaction was not approved for a potentially temporary reason (insufficient funds, authentication required, risk-based decline) rather than a definitive rejection. A soft decline is an issuer-side event; a false positive is a merchant-side fraud detection error.

How does [3DS2] reduce false positives compared to rule-based fraud systems?

3DS2 reduces false positives in two ways. First, it shifts the authentication decision to the issuing bank, which has more cardholder context than the merchant, the issuer knows the cardholder's account history, typical spending patterns, and current account status in a way the merchant never can. Issuers applying Risk-Based Authentication with this richer context are more accurate at distinguishing legitimate from fraudulent transactions.

Related Terms

Fraud Scoring

Fraud scoring assigns a risk score to each transaction using device, behavioral, and historical signals to identify likely fraud before a card is charged.

Learn more →

Risk-Based Authentication (RBA)

Risk-Based Authentication adjusts verification requirements based on a transaction's calculated fraud risk score and the surrounding contextual signals.

Learn more →

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