AI in Finance: Can FinTech Innovate Faster Than Fraudsters?

Artificial Intelligence is steadily reshaping the global financial sector. Banks, insurance companies, mobile money operators, FinTech firms and payment platforms increasingly use AI to detect fraud, assess risk, authenticate customers, automate services, analyse transactions and improve customer experience. Yet the same technology helping financial institutions protect money is becoming increasingly available to criminals trying to steal it. This emerging contest between intelligent financial systems and intelligent financial crime deserves far greater public attention.

I do not come from a traditional finance or economics background. My interest in this subject comes from Artificial Intelligence, particularly how AI can be responsibly deployed to solve real-world problems while its risks are properly governed. As an AI Engineer who has been invited to speak on AI governance, risk and regulation in the FinTech sector in Frankfurt this October, I believe we need a broader public conversation about where AI-driven finance is taking us, especially as financial services become increasingly digital across Africa and the rest of the world.

FinTech Is Already Changing How We Handle Money

Financial technology, commonly known as FinTech, has fundamentally changed the relationship between people and financial services. Across Africa, one does not need to look far to see this transformation. Kenya's M-PESA helped pioneer large-scale mobile money services, while Ghana's mobile money ecosystem has become deeply embedded in everyday economic life. Nigeria has similarly experienced rapid expansion of digital payment platforms, mobile banking and FinTech services.

The transformation is much bigger than Africa. Digital wallets, instant payments, online banking and AI-assisted financial services have become commonplace across Europe, North America, Asia and other parts of the world. Global payment companies and financial institutions increasingly deploy machine learning and AI systems to identify suspicious transactions, detect unusual behavioural patterns and stop fraudulent payments before money disappears.

The scale of digital finance is remarkable. According to the GSM Association (GSMA), more than US$2 trillion flowed through mobile money accounts globally in 2025, while registered mobile money accounts reached approximately 2.3 billion. Africa remains at the heart of this mobile money revolution, but the wider lesson is global: money is becoming increasingly digital, interconnected and dependent on technological infrastructure.

This presents enormous opportunities. A farmer in rural Ghana or Kenya can receive payment without travelling several kilometers to a bank. A small business can transact instantly with customers. Families can transfer money across communities, while previously underserved populations can participate more easily in the formal financial system. AI can potentially strengthen these systems further through faster fraud detection, improved credit assessment, personalised services and better cybersecurity.

But the Fraudsters Also Have AI
Here lies the uncomfortable part of the AI revolution. The financial institution is learning, but so is the criminal.

Generative AI can help criminals produce convincing phishing messages, imitate voices, manipulate images and videos, forge documents and automate social engineering attacks. Deepfake technology raises an even more disturbing possibility: what happens when a bank customer, company executive or family member appears to be speaking on a video call or voice message but the person being seen or heard is actually an AI-generated impersonation?

This threat is not theoretical. The United States Federal Reserve has warned that generative AI and deepfakes can amplify identity fraud, while the Federal Bureau of Investigation reported more than US$16 billion in losses from reported internet crime in the United States in 2024 alone. Across Africa, INTERPOL's 2026 African Cyberthreat Assessment found that AI was enabling 55 percent of reported cybercrimes, making attacks faster, more scalable and increasingly difficult to detect.

We are therefore entering an era in which AI may simultaneously serve as part of the defence and part of the attack. A FinTech company can use machine learning to detect an unusual transaction within seconds, while a criminal network can use AI to create thousands of personalised fraudulent messages, synthetic identities or sophisticated scams at unprecedented speed.

Africa Has Much to Gain, and Much to Protect

For Africa, the stakes are particularly high because digital finance has sometimes leapfrogged traditional financial infrastructure. Millions of people who never had conventional bank accounts now conduct transactions through mobile phones. This is one of the continent's great technological achievements, but rapid adoption must be accompanied by equally serious investments in digital security, regulation, institutional capacity and consumer awareness.

AI governance must therefore become an integral part of Africa's expanding digital financial ecosystem. It is not enough for a bank or FinTech company to deploy an AI system simply because it improves efficiency or profitability. Institutions must understand what data their systems use, how consequential decisions are made, whether models may produce discriminatory or biased outcomes, who remains accountable for those decisions, and what happens when an AI system fails or causes financial harm. African regulators must develop governance frameworks that protect consumers without suffocating home-grown innovation. Responsible AI in finance should ultimately mean innovation with transparency, security, appropriate human oversight and clear accountability.

This responsibility cannot rest on regulators alone. Central banks, telecommunications companies, commercial banks, FinTech providers and technology developers must strengthen fraud detection, cybersecurity testing and identity verification as AI-enabled attacks become more sophisticated. High-risk or unusual transactions should not simply be left to algorithms without appropriate safeguards and human intervention. Authentication systems must also evolve beyond passwords and basic identity checks as deepfakes and synthetic identities become increasingly convincing.

There is equally an urgent need for public education. The strongest cybersecurity system can still be defeated when a frightened or unsuspecting customer voluntarily gives a fraudster a password, verification code or mobile money PIN. Financial literacy in the AI era must therefore include digital and AI literacy. People need to understand that seeing a face, hearing a familiar voice or receiving a professionally written message is no longer sufficient proof of identity.

Financial cybercrime is also inherently transnational. A fraudster can operate in one country, use digital infrastructure in another, target victims thousands of kilometers away and move stolen funds through multiple jurisdictions within minutes. African regulators, law enforcement agencies, financial institutions, and technology companies therefore need stronger cross-border intelligence sharing and cooperation, while also working with international partners confronting similar threats.

Innovation Must Not Outrun Responsibility

I remain optimistic about AI in finance. Used responsibly, AI can help financial institutions identify fraud earlier, reduce operational costs, improve services, expand financial inclusion and make digital financial systems more resilient. For Africa in particular, combining FinTech innovation with responsible AI could help extend useful financial services to millions of people who remain underserved by conventional banking.

But technological capability alone cannot be our measure of progress. We must also ask whether AI systems are secure, sufficiently transparent and explainable where necessary, properly governed and accountable when something goes wrong. Africa should not merely become a large market for AI-powered financial products developed elsewhere. The continent must also build the regulatory expertise, technical capacity, local innovation ecosystems and institutional safeguards needed to shape how AI is deployed in its own financial future.

Conclusion
The future of finance will therefore not simply be about who develops the smartest algorithm. It will also depend on who can build and maintain public trust. The challenge before the global FinTech community, and Africa in particular, is therefore clear: innovate boldly, govern intelligently and never allow technological speed to outrun institutional responsibility.

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