Reduce account-to-account (A2A) payments fraud and improve customer experience

How is your business balancing fraud and security while protecting your brand in the changing A2A payment landscape?

The sharp increase in instant A2A transactions, such as person-to-person (P2P) payments, digital wallets and QR codes, are becoming the target of fraudsters around the world. Issuers must refocus their fraud and security strategies to include this rapidly growing change and risk.

$9.87T

Estimated global P2P market in 2030

– Precedence Research

60%

Of people worldwide will use digital wallets by 2026

– Computer Weekly

$3T

Estimated global spending by QR codes by 2025

– QR Code Tiger

Know when an A2A transaction is legitimate or the result of a scam

A2A Transaction Fraud Monitoring is a powerful AI solution that detects fraud across payment rails. This highly accurate solution protects you and your customers from attacks such as social engineering, authorized push payments fraud and account takeover (ATO). Output scores indicate likelihood of fraud and scams in real time.

The solution is built quickly using your historical data and ready to deploy in six to eight weeks.

Deploy in any market worldwide and start seeing results right away

Increase real-time fraud detection

Improve customer experience and protect your brand

Be transparent with innovative explainable models

Save time and money with fast easy model build and deployment

Simplify rules with a customizable Rules Management module

Powered by Brighterion AI

What makes us different?

Full stack, state-of-the-art machine learning toolkit allows for custom model development in 6-8 weeks
Unrivaled model building, deployment speed and scalability, allowing for easy implementation, lightning-fast response times (<10 ms*) and resiliency
Rapid deployment is enabled using cloud-based API, multi-tenant, PCI-certified MC Connect integrated modules
A modern and configurable interface with customizable rules, case management and insights modules
Industry-leading data responsibility practice, with embedded human-centered data innovation and product design principles

* 100-120 ms in the cloud or 10 ms on-premise