The fintech industry in 2040: What trends will shape banking over the next 15 years?
Generative AI with autonomous financial agents, quantum computing capable of spotting fraud in seconds, and banking services embedded in health or e-commerce apps. According to 'Fintech 2040', a report drawn up by BNPL provider Riverty, this could well be how fintech evolves over the next two decades. The study suggests a world where the boundaries between payments, lending, insurance and investment fade, and financial services become an integral part of people’s everyday digital lives.
The report reviews the ‘order-to-cash’ (OTC) cycle, from first customer contact to post-purchase communication, insurance or dispute resolution. Despite the variety of technologies in play, two themes dominate: ever more personalized customer experiences and greater automation of banking processes. Users will be able to make financial decisions on the spot without having to log into banking apps, while financial agents will process vast amounts of data in real time. Transparency, flexibility and seamless service will become the norm.
AI for everything
Artificial intelligence (AI) will be the dominant trend over the coming 15 years. By 2030, it could save the banking and fintech industry an estimated $1 trillion through AI agents capable of negotiating deals, making investments and autonomously detecting fraud. This is the natural evolution of today’s generative AI into services that go far beyond chatbots, ultimately enabling independent decision-making. Tech giants such as Google, Apple, and OpenAI are already racing to develop these systems.
While current AI tools tend to revolve around chatbots to make customer service more user-friendly, the next generation will embed automated assistants into daily financial management. These agents will be able to recommend financial products based on a client’s risk tolerance or even mood, and come up with tailor-made banking and investment solutions. Data collection on user behavior will deepen this tailoring.
On the security front, AI will hone fraud detection capabilities by spotting unusual patterns more quickly. Biometric innovations will further fortify this, from keystroke rhythm analysis to mobile usage patterns, adding further layers of authentication. Riverty projects that the AI cybersecurity market will grow from $28.5 billion today to $177 billion by 2034, and could even reach $600 billion by 2040 if current trends continue.
Embedded finance
AI-driven personalization will also accelerate the rise of embedded finance, where banking services integrate directly into other industries. By combining contextual data—location, device activity, shopping habits or brand loyalty—companies can deliver tailored financial offers in real time.
This trend will enable services such as installment payments or insurance purchase at the point of sale. Thanks to APIs, financial products can be embedded in apps across commerce, healthcare or education. As these integrations grow more autonomous, the existing boundaries between payments, loans, insurance, and investments will fade. A customer might reallocate part of their pension to cover a purchase or tap an investment opportunity, all without switching to a proper banking app. Flexibility, fluidity and customization will be the hallmarks of these services.
Quantum computing
AI is dominating the headlines today, but it is quantum computing that could well shape the decades ahead. Research is currently led by Google and IBM, as both push toward the first commercial-grade quantum computer. The challenge remains error correction, since the materials involved are highly unstable. Still, forecasts point to commercial availability by the end of the decade. Fittingly, 2025 has been declared the International Year of Quantum Science and Technologies.
For finance, the promise lies in exponential gains in processing power, allowing systems to instantly cross-check enormous data sets, thus improving risk models or fraud detection. Tasks that currently take hours of manual oversight could be completed in just seconds, producing more precise real-time predictions.
For customers and merchants, quantum analysis of global price trends or browsing histories could yield hyper-personalized recommendations and help merchants adjust inventory or promotions to shifting demand. Combined with AI automation, this points to a future of tailor-made shopping and financial experiences.
Yet quantum computing also carries certain risks. The technology could render today’s cryptographic protocols obsolete and threaten existing security systems. As a result, cybersecurity techniques must evolve in step with these new threats, including the possibility of ‘quantum cybercrime.’
Together with existing trends such as decentralized finance and cryptocurrencies, these innovations herald a new-look financial landscape. Customers will expect more transparency, inclusion, and fluidity, while financial transactions will become highly automated and hyper-personalized.