Payment Fraud Prevention

Payment Fraud Prevention

Less fraud. Fewer false positives.
In real time.

Prevent scam and fraud attempts in real time with a comprehensive solution for banking fraud operations. Pre-built artificial intelligence (AI) models, robust case management and intuitive investigative dashboards detect and stop fraudulent payments from authorized push payment scams, device compromise, account takeover and more — ensuring compliance with the latest regulations.

Trusted technology partners

Reduction in false positives

0 %

Vyntra customer results

Savings in operating costs

0 %

Vyntra customer results

Individuals protected worldwide

0 m

Across 130+ institutions in 60+ countries

Fraud on the rise

Fraudsters are stepping up their game. Every day.

As digital interactions take the lead, instant settlement is the new norm for digital payment schemes. Fraudsters are upping their game, getting more cunning every day, deploying phishing attacks, harvesting stolen credentials, and exploiting data breaches to cause real financial losses and lasting reputational damage. It’s time to act swiftly and stay ahead — with a proactive approach that identifies both known and emerging fraud patterns, and real-time detection of fraudulent transactions.

Detect & prevent in real time

With pre-built AI models

Reduce false positives

Using powerful behavioral analytics and profiling

Uncover new & emerging threats

Known and unknown fraud patterns across a constantly evolving cybercrime landscape

Faster, flexible deployment

To suit your needs — in cloud, on premise
 

Capability 01

Stop fraudulent transactions in real time

The solution integrates within your payment processing flow and analyzes payments through risk scoring models to accurately detect suspicious behaviors — monitoring large volumes of transactions in real time.

What you get

Capability 02

Pre-built AI models

Our AI and machine learning models do heavy lifting: forget complex and expensive data science projects. Pre-built models detect fraud more accurately with lower false positives, helping you start preventing fraud quickly.

What you get

Capability 03

Powerful case management

Alerts are raised in real time, routed to the appropriate team, and intuitively contextualized — so analysts immediately understand every alert.

What you get

Capability 04

Unrivaled investigative tool

Standardized and intuitive widget-based dashboards help you visualize, understand and contextualize transactional behavior.

What you get

Go deeper

Explore the use cases behind the solution.

Use Case

The customer approved it. That doesn’t make it legitimate — four attack patterns, from romance fraud to Business Email Compromise.

Use Case

Valid credentials, invalid owner — three takeover methods, from phishing and RATs to bot-driven credential stuffing.

Use Case

Instant means irreversible — fraud detection that decides in milliseconds, built for the clock of instant payment rails.

Read the use case →

Use Case

It takes a network to defeat a network — one member’s fraud sighting becomes every member’s protection.

GET IN TOUCH

Stop payment fraud
in real time.

See how Vyntra detects and stops fraudulent payments before funds leave — pre-built AI models, behavioral profiling, explainable investigations and automated customer callbacks. In cloud or on premise.

FAQs​

What is Business Email Compromise?
Business Email Compromise (BEC) is a form of social engineering in which a fraudster impersonates a senior employee, supplier or trusted contact to convince someone to make a fraudulent payment. Because the victim may authorize the payment themselves, BEC can bypass conventional login and authentication controls. Vyntra helps by analyzing the payment, beneficiary and surrounding behavior for unusual patterns before funds leave.

Real-time payment fraud detection analyzes a transaction while it is still in progress and assigns it a risk score before it is completed. AI models and behavioral analytics can identify suspicious changes in customer behavior, payment patterns and beneficiary activity that may indicate online payment fraud. Vyntra applies this analysis within the payment flow, helping banks detect unauthorized transactions while allowing legitimate payments to continue.

No. Payment fraud detection works alongside cybersecurity controls such as multi-factor authentication, two-factor authentication and tokenization. Authentication confirms who is accessing an account, while tokenization helps protect sensitive payment data. Fraud detection provides a separate layer of protection by assessing whether the payment itself appears suspicious, even when the customer has successfully authenticated.
Banks can reduce false positives by combining real-time risk scoring with customer profiling, behavioral analytics and clear investigation context. This makes it easier to distinguish genuinely suspicious activity from normal changes in customer behavior. Vyntra supports this by contextualizing alerts, routing them to the appropriate team and helping analysts prioritize cases that require manual review.