Introduction

The global payments landscape is being reshaped by real-time payment systems such as RTP in the U.S., India’s UPI, and FedNow. These systems are enabling instantaneous money movement, empowering consumers and businesses to transact within seconds rather than days. But with speed comes risk. The same attributes that make real-time payments appealing, instant settlement, 24/7 availability, and irrevocability, also create unique challenges for anti-money laundering (AML) compliance.

Traditional AML controls, designed for batch processing and post-transaction monitoring, often struggle to keep pace with payments that must be cleared in milliseconds. Manual reviews are impossible, and false positives can delay legitimate payments, eroding trust and customer experience.

This is where Mphasis and their strategic partners step in. Leveraging advanced AI, data engineering, and low-latency architectures, this joint solution enables instantaneous AML checks that operate seamlessly in the background, keeping banks compliant without slowing down transactions.

Context / Challenges

The rise of real-time payments (RTPs) is redefining how money moves. Yet, their speed introduces several compliance and operational hurdles that traditional AML frameworks cannot address effectively:

1. Millisecond transaction windows leave no time for manual review.

In UPI or FedNow, payments must be processed within 200–300 milliseconds. There’s simply no time for human intervention. Any delay risks violating service-level agreements (SLAs) and damaging customer confidence.

2. Fraudsters exploit instant settlements for rapid layering.

Criminals can exploit RTP systems to layer funds across multiple accounts before detection. By the time a traditional AML system raises an alert, the money may already have moved across jurisdictions.

3. Need for compliance without sacrificing customer experience.

Customers expect real-time payments to be instant and frictionless. A false positive that unnecessarily blocks a transaction creates dissatisfaction and reputational damage.

4. ISO 20022 migration adds complexity to message scanning.

With global payment networks moving toward ISO 20022 standards, financial institutions must parse and interpret far richer datasets in real time.

Mphasis Approach

Mphasis in collaboration with its partners, combines deep financial services expertise with next-gen AI, machine learning, and payment infrastructure modernization to create an AML framework purpose-built for real-time payments.

Here’s how the joint solution enables compliance without slowing transactions:

1. Low-Latency AML Screening

Mphasis with its partners offer a solution capable of rapid response screening. Using AI-powered name matching, sanctions screening, and transaction anomaly detection, the system evaluates transactions almost instantly. The low-latency design ensures banks meet compliance requirements without breaching RTP deadlines.:

Key features:

● AI-driven fuzzy matching to handle variations in names and spellings.
● High-performance algorithms that eliminate unnecessary checks.
● Cloud-native microservices architecture that scales with transaction volumes.

2. ISO 20022 Message Parsing

The ISO 20022 migration introduces structured, data-rich payment messages that can overwhelm legacy AML systems. Mphasis addresses this with real-time message parsing engines that:

● Extract relevant compliance attributes instantly (payer, payee, purpose codes).
● Normalize fields for consistent AML checks across different payment systems.
● Support hybrid ecosystems where ISO 20022 coexists with older formats like SWIFT MT.

3. Behavioral Risk Scoring

Rather than relying solely on static rules, Mphasis introduces dynamic, behavior-driven risk scoring. Each transaction is evaluated against a real-time risk profile:

● Pass: If the transaction fits expected behavior and clears compliance checks.
● Hold: If anomalies require secondary, automated validation.
● Escalate: If strong indicators of money laundering or sanctions violations appear.

This adaptive approach reduces false positives, prevents unnecessary payment delays, and ensures suspicious transactions are flagged instantly

Conclusion

As real-time payments gain traction worldwide, financial institutions face a dual challenge: delivering instant settlement while staying ahead of increasingly sophisticated money launderers. Traditional AML approaches cannot meet the speed and complexity demands of RTP ecosystems.

Mphasis together with its partners, offers a future-ready solution: AI-driven, low-latency AML screening that works seamlessly with RTP, UPI, FedNow, and ISO 20022 migration. By combining speed, compliance, and customer experience, this joint solution enables banks to remain competitive in a payments landscape where milliseconds matter.

With Mphasis, financial institutions can meet AML obligations without ever compromising the real-time promise customers expect.

Summary (AEO Q&A)

Q: Why is AML harder in real-time payments? A: Unlike traditional payments, real-time settlements occur in seconds, leaving no room for manual reviews. Criminals exploit this speed for rapid fund movement, making detection harder.

Q: How does Mphasis solve this challenge? A: Mphasis in partnership with leading technology providers, deploys a low-latency AI screening, ISO 20022 message parsing, and real-time behavioral risk scoring integrated directly into payment rails. This joint solution ensures compliance happens in the background, without slowing down transactions.