Shared intelligence will define the future of fraud prevention

South Africa is not losing the fight against fraud because it lacks technology. It is being challenged because fraud is evolving faster than institutions can respond in isolation.

By Salomon Erasmus, regional MD of Network International Southern Africa

In today’s real-time payments economy, the organisations that will lead in fraud prevention will not simply have the best technology—they will be those that collaborate most effectively.

Artificial intelligence is transforming how fraud is detected, but technology alone is not enough. The next frontier of fraud prevention lies in shared intelligence across banks, payment service providers, fintechs, acquirers, merchants and regulators. Fraudsters already operate as connected networks, sharing techniques, exploiting vulnerabilities and adapting rapidly. The financial services industry must become just as connected if it is to stay ahead.

South Africa’s payments landscape is evolving at an unprecedented pace. Instant payments through PayShap, digital wallets, mobile-first banking, Open Banking initiatives and embedded finance are making payments faster, simpler and more accessible than ever before. These innovations are driving financial inclusion and creating better customer experiences, but they are also introducing new fraud vectors.

The same speed that allows consumers to make payments in seconds dramatically reduces the time available to identify and stop fraudulent activity. Fraud prevention can no longer rely on retrospective investigations or isolated monitoring. It must become predictive, collaborative and intelligence-led.

A payments ecosystem challenge, not just a banking challenge

As a payments technology partner working across issuers, acquirers, fintechs and merchants, Network International has a unique perspective on how fraud moves through the payments ecosystem. Fraud rarely begins and ends within a single institution. Different participants see different parts of the customer journey—from digital onboarding and payment initiation to merchant acceptance, settlement and disputes.

Merchants are often among the first to encounter emerging fraud patterns, while payment providers and acquirers may identify abnormal transaction behaviour long before it reaches an issuing bank. Yet too often, these valuable insights remain confined within individual organisations.

This fragmented view creates opportunities for criminals to exploit the gaps between institutions.

South Africa is one of Africa’s most digitally advanced payments markets, making it an important indicator of fraud trends likely to emerge across the continent. As digital payment adoption accelerates across Africa, so too does the need for trusted collaboration and shared intelligence.

Isolation slows detection

Many financial institutions, payment providers and merchants continue to rely primarily on their own proprietary fraud detection systems and internal datasets. While these investments strengthen individual organisations, they inevitably limit visibility across the wider payments ecosystem.

INTERPOL’s African Cyberthreat Assessment continues to highlight how organised criminal networks collaborate across borders, sharing stolen identities, compromised credentials, mule accounts and increasingly sophisticated fraud methodologies. Criminals operate collectively, learning from every successful attack.

The industry, however, often does not.

Fraud, cybersecurity, compliance and operational risk teams frequently analyse different datasets within their own organisations. Valuable lessons are learned, but too often they remain trapped within institutional boundaries instead of strengthening the wider ecosystem.

In a real-time payments environment, every delay in recognising emerging fraud patterns increases financial losses.

AI is only as powerful as the intelligence behind it

AI has become one of the industry’s most powerful tools for identifying fraud. Today’s AI-driven models continuously analyse customer behaviour, login activity, device usage, transaction values, beneficiary changes and payment patterns to identify anomalies that would be impossible for humans to detect at scale.

However, AI is only as effective as the intelligence it learns from.

A model trained exclusively on one institution’s historical data becomes highly effective at recognising patterns it has already experienced. But fraud evolves across markets, organisations and payment channels – not within the boundaries of a single institution.

This means even the most sophisticated AI can struggle to identify emerging threats that first appear elsewhere.

The future therefore lies not simply in deploying better AI, but in providing AI with broader, richer and more representative intelligence.

Global fraud intelligence networks have already demonstrated the value of this approach. When anonymised behavioural signals and transaction patterns are shared responsibly across thousands of institutions, fraud models become significantly better at recognising new attack methods before they spread widely.

For South Africa, the lesson is clear: collaboration enables institutions to detect fraud earlier without compromising customer privacy or individual decision-making.

Collaboration extends beyond technology

Technology alone will not solve this challenge.

AI-driven fraud prevention still depends on experienced analysts, robust governance, effective alert management and highly specialised fraud expertise. These capabilities remain expensive and are increasingly difficult to source.

Shared fraud infrastructure offers a practical solution, particularly for smaller banks, fintechs and payment providers. By pooling intelligence, expertise and infrastructure while maintaining control over their own risk decisions, organisations can strengthen fraud detection without each needing to build identical capabilities independently.

Trust, however, remains fundamental.

Effective collaboration requires strong governance, clear data minimisation principles, anonymisation, auditability and regulatory alignment. Institutions do not need to exchange customer identities or commercially sensitive information to benefit from shared intelligence. The objective is not to centralise customer data it is to responsibly share risk signals that enable faster and more informed decisions.

The next competitive advantage

Fraud visibility must extend well beyond traditional banking. Payment service providers, acquirers, fintechs and merchants all observe different signals throughout the payment lifecycle. Combining these perspectives creates a far more complete understanding of emerging fraud than any single organisation can achieve independently.

The organisations that will lead the next generation of fraud prevention will not necessarily have the largest security budgets or the most advanced AI platforms. They will be those that combine technology with trusted partnerships, richer intelligence and faster collective learning.

Fraudsters already collaborate. They share techniques, adapt quickly and exploit every weakness across the payments ecosystem.

The financial services industry must do the same.

For South Africa – and increasingly for the rest of Africa – the question is no longer whether collaboration is necessary. It is how quickly banks, payment providers, fintechs, merchants and regulators can work together to build a more intelligent, resilient and secure payments ecosystem.

In a real-time economy, speed matters. But shared intelligence will matter even more.

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