Instant payments and fraud prevention: why AI is becoming indispensable

Instant payments: speed as both value and vulnerability

Instant payments deliver clear benefits for consumers and businesses: immediacy, convenience and improved liquidity management.

But they also compress the fraud response window dramatically.

As highlighted in the EPC Payments Threats and Fraud Trends Report, faster execution amplifies exposure to authorised push payment scams, impersonation fraud and other forms of social engineering where the victim initiates the transfer themselves.

In short: the payment is legitimate, but the intent is manipulated.

This is consistent with findings from the latest joint ECB and EBA report on payment fraud, which confirms that manipulation of the payer now accounts for the majority of fraudulent credit transfers in value terms across the EU.

Fraud prevention is moving from detection to real-time decisioning

The operational reality of instant payments is straightforward: institutions must assess identity, intent and risk eligibility in real time.

This is where AI is increasingly seen not as an innovation layer, but as a necessity.

The recent AI in Action: Global survey on fraud and financial crime, published by Finextra Research in association with ACI Worldwide underlines how rapidly the industry is shifting:

• 51% of organisations have already deployed AI capabilities in fraud prevention
• 47% are implementing AI, with go-live planned within the next 24 months
• yet only 19% operate with full AI autonomy, meaning human oversight remains dominant

The direction of travel is clear: fraud strategies must evolve from reactive controls to adaptive, real-time orchestration across payment channels.

New risks, new constraints: trust, regulation and data governance

AI offers significant potential, but its integration comes with structural challenges.

The survey identifies compliance with emerging AI regulation as the top internal hurdle for organisations adopting AI in fraud prevention.

More strikingly, respondents rank data privacy risks in AI training as the leading emerging threat, even ahead of fraud itself.

This reinforces a central message for the sector: effective fraud prevention requires not only better models, but also strong governance frameworks, ethical data practices and explainable decision-making.

In an increasingly fragmented regulatory environment, trust in AI systems will be as important as technical performance.

Collaboration and intelligence sharing: a sector-wide imperative

Fraud is rarely confined to one institution or one jurisdiction.

Europol has repeatedly stressed that cyber-enabled fraud thrives on fragmentation, speed and cross-border laundering structures. Addressing it requires stronger cooperation between banks, PSPs, fintechs, supervisors and infrastructure providers.

This is why the ABBL places collaboration at the heart of Luxembourg’s payments ecosystem.

Through initiatives such as the ABBL Bank CEOs–FinTechs Speed Meeting 2026, the ABBL actively supports structured dialogue and concrete partnerships that strengthen operational resilience and innovation capacity across the sector.

Fraud prevention increasingly depends on shared intelligence, interoperable systems and coordinated response frameworks.

Looking ahead: innovation must scale with security

The coming months will bring further transformation in Luxembourg’s payments landscape, including the rollout of Wero, the new European digital wallet expected from July 2026. 

Wero reflects the broader move towards account-to-account instant infrastructure at European scale, offering new opportunities for consumers and merchants.

At the same time, it reinforces the importance of ensuring that innovation is delivered with robust fraud prevention, clear accountability and trusted implementation.

As explored in the ABBL’s analysis of the growth of payment and e-money institutions, the ecosystem is diversifying rapidly.

Success will depend not on novelty alone, but on secure execution, governance and collaboration.