# Transaction Fraud Monitoring
source: https://developer.mastercard.com/brighterion/product/transaction-fraud-monitoring/index.md

### Overview {#overview}

###### The most efficient and effective way to fight transaction-level fraud {#the-most-efficient-and-effective-way-to-fight-transaction-level-fraud}

Transaction Fraud Monitoring scores each payment transaction for fraud risk in real time. You send transaction data through a cloud-based API and receive a risk score that you can use to approve, decline, or review the transaction based on your own score thresholds.

The machine learning models are trained on Mastercard global network intelligence and combine transaction, behavior, threat, and market data. This helps financial institutions stop fraud earlier while approving more genuine transactions and reducing false declines.

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### Benefits {#benefits}

Increase profits and strengthen customer relationships
![Higher revenue](https://static.developer.mastercard.com/content/brighterion/uploads/higher_revenue.svg)

###### Higher revenue {#higher-revenue}

Approve more genuine transactions without increasing risk exposure, and gain share of wallet by becoming the go-to payment choice for online shopping
![Greater loyalty](https://static.developer.mastercard.com/content/brighterion/uploads/greater_loyalty.svg)

###### Greater loyalty {#greater-loyalty}

Reduce cardholder inconvenience from false declines and create seamlesss shopping experiences
![Lower costs](https://static.developer.mastercard.com/content/brighterion/uploads/lower_costs.svg)

###### Lower costs {#lower-costs}

Decrease customer service costs due to more approved transactions and retain revenue formerly lost to fraud chargebacks
![Easy deployment](https://static.developer.mastercard.com/content/brighterion/uploads/easy_deployment.svg)

###### Easy deployment {#easy-deployment}

Production-ready for a light lift via three simple steps through a cloud-based API

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### How it works {#how-it-works}

Earlier, more accurate detection keeps merchant profiles clean - increasing approval rates at downstream decision points.

![How it works](https://static.developer.mastercard.com/content/brighterion/uploads/how_it_works.svg)

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### Use cases {#use-cases}

Examples of how financial institutions use Transaction Fraud Monitoring to stop fraud without blocking genuine customers.

###### Stop card-not-present fraud {#stop-card-not-present-fraud}

A fraudster uses stolen card details to make online purchases across several merchants. Each transaction is scored in real time, and high-risk transactions are declined or sent for review before they are approved.

###### Reduce false declines {#reduce-false-declines}

A genuine cardholder makes an unusual purchase while traveling abroad. Instead of relying on a single rule, the risk score considers wider behavior and network data, so the transaction can be approved without unnecessary friction.

###### Detect card testing attacks {#detect-card-testing-attacks}

Fraudsters submit many small authorizations to check whether stolen card numbers are valid. Real-time scoring helps identify these patterns and block them before larger fraudulent purchases follow.

###### Customer example {#customer-example}

An acquirer using Transaction Fraud Monitoring increased approval rates by 11.25% while achieving 5.4x fraud detection.

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### Why use it {#why-use-it}

Financial institutions need the right tools to protect themselves and their customers in a dynamic fraud environment while providing a frictionless experience.

### 93%

acquirers who experienced increased transaction fraud between 2020 and 2021

PYMNTS.com, AI in focus: The rise against payments fraud, December 2021

### $49 billion

is the estimated loss to payment fraud in 2030

NILSON, Nilson Report Issue 1209: Card Fraud, December 2021

### 73%

card fraud losses in 2023 were due to CNP fraud

Insider Intelligence, Card-not-present fraud to make up 73% of card payment fraud, January 2023

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### Key features {#key-features}

![Intuitive user interface](https://static.developer.mastercard.com/content/brighterion/uploads/intuitive_ui.svg)

###### Intuitive user interface {#intuitive-user-interface}

Use an intuitive, customizable interface allowing organizations to trigger specific actions based on score thresholds
![Model training](https://static.developer.mastercard.com/content/brighterion/uploads/model_training.svg)

###### Model training {#model-training}

Proprietary machine learning models are trained on Mastercard global network intelligence
![Real-time protection](https://static.developer.mastercard.com/content/brighterion/uploads/realtime_protection.svg)

###### Real-time protection {#real-time-protection}

Layering global transaction, behavior, threat, and market data to detect and stop evolving fraud schemes across the entire payment ecosystem