At the same time, AI adoption across the financial sector is accelerating. Banks are automating fraud detection, credit assessments, and real-time decision-making using AI models capable of analyzing vast amounts of transaction data within milliseconds.

But as the technology becomes smarter, so do the threats.

Deepfakes, synthetic identities, and AI-generated fraud are growing rapidly – and the same technology used to protect financial systems is also being used to attack them. This creates an entirely new type of security challenge where the speed of innovation itself risks becoming a vulnerability.

This is where the next major competitive advantage will be decided. Not in individual AI models or payment platforms, but in the ability to build resilient systems where software, data, security, cloud infrastructure, and user experience work seamlessly together – even as the threat landscape changes in real time.

When Payment Flows Become Critical Infrastructure

Sweden has long been at the forefront of digital payments. Swish is used by almost the entire population, while new EU regulations such as the Instant Payments Regulation are accelerating the shift toward 24/7 real-time payments.

ISO 20022 is a key part of that development. The new standard makes it possible to include significantly more information in every payment, opening the door to smarter automation, improved traceability, and more effective AI-driven analysis.

For banks and fintech companies, this creates major opportunities. AI can identify suspicious behavior in real time, analyze thousands of data points simultaneously, and stop fraud before money is moved.

But it also introduces greater complexity.

Systems that were previously relatively isolated must now integrate with more stakeholders, more APIs, and more real-time data flows. At the same time, these solutions must operate around the clock, comply with regulatory requirements, and deliver a seamless user experience – even as the underlying technology becomes increasingly advanced.

This is also why the line between traditional banks and fintech companies is becoming less distinct. The same technological building blocks are now used across embedded finance, BNPL solutions, open banking, and modern payment platforms. Innovation is increasingly driven by organizations with deep expertise in software development, data, and digital infrastructure.

AI-Driven Fraud Is Growing as Fast as AI-Based Defense

Alongside the ISO transition, another race is unfolding – the battle against AI-powered fraud.

Sweden’s financial authorities, including the Financial Supervisory Authority and the central bank, have already warned about how deepfake voices, synthetic identities, and AI-generated attacks are being used to deceive both individuals and businesses. Fraud is becoming more scalable, more personalized, and significantly harder to detect.

What makes the situation especially complex is that the same technology is being used on both sides.

AI is being used to identify fraud through behavioral analysis and anomaly detection. At the same time, fraudsters are using AI to imitate human behavior, create convincing identities, and automate attacks at scale.

That is why many are now talking about an “AI fraud paradox” – machines fighting machines, where the line between legitimate and malicious activity becomes increasingly difficult to define.

As a result, banks and fintech companies need to build entirely new types of defenses. Data must move securely between systems and security domains. AI models must be continuously updated as threats evolve. And development teams must be able to deliver new functionality quickly without compromising security or regulatory compliance.

The Paradox: The Smarter the Systems Become, the Smarter the Attacks Become

This is where the AI fraud paradox truly emerges.

ISO 20022 and AI create better opportunities to detect fraud through richer data and smarter analytics. But the same data and the same technologies also give fraudsters more opportunities to identify weaknesses and launch increasingly sophisticated attacks.

This leaves banks facing a difficult choice:

• Maximize AI adoption to achieve faster innovation and stronger real-time capabilities.
• Or introduce more control mechanisms and defensive layers – at the risk of slower development and a poorer user experience.

In practice, this is no longer just a technology issue. Questions surrounding AI, verification, data flows, and cloud strategy have simultaneously become business-critical and regulatory concerns.

It also means that entirely new forms of expertise are becoming essential. Building resilient architectures, translating PSD3 requirements into practical solutions, and creating systems capable of handling both rapid innovation and strict security demands will become some of the financial sector’s most important challenges in the years ahead.

How the Financial Sector Can Avoid the AI Fraud Paradox

Building long-term sustainable payment solutions requires more than new AI models and modern APIs.

Three things will be especially critical:

1. Closer Collaboration Between Banks and Fintech Companies

Innovation is moving faster than many traditional organizations can adapt to. That is why closer collaboration is needed between banks, fintech companies, and regulators – from early prototypes to integration, operations, and security.

2. Industrial-Grade Software Maturity

Proofs of concept are no longer enough. AI solutions must be continuously tested, quality assured, and refined as the threat landscape evolves. This applies to everything from deepfake detection and behavioral analytics to UX and real-time transaction flows.

Ultimately, success will not be determined by who builds the fastest – but by who builds solutions that remain reliable over time.

3. Security and Resilience Must Be Built In from the Start

Security cannot be added afterward. From day one, architectures must be designed to support:

• Behavior-based verification,
• AI-driven defense mechanisms,
• Isolation of third-party risks,
• Systems capable of operating even in degraded conditions.

The challenge is balancing innovation, usability, and security – without creating unnecessary friction for customers.

A New Payment Ecosystem Requires New Technology Partners 

Sweden is facing yet another crossroads in the digitalization of the financial sector. Maximizing AI speed can create new security risks, while being overly cautious may slow down innovation.

To succeed, organizations need partners capable of turning ISO 20022, AI, and real-time data into practical solutions – secure, resilient, and built for constant change.

At HiQ, we work with complex software development, system integration, data and cloud architecture, and user-centric digital solutions in environments where security and reliability are critical. We see a growing demand for technology partners that can combine rapid innovation with regulatory compliance, cybersecurity, and real-time AI capabilities.

Want to discuss how to build payment and AI solutions that meet today’s user expectations while preparing for tomorrow’s threat landscape? Get in touch!