How AI is shaping the future of fintech
'AI is enabling personalised finance, using real-time data to tailor products, insights and decisions to individual customer behaviours.' Photograph: Getty Images
The shift from simple digitalisation to full scale artificial intelligence-driven transformation means AI is no longer an add on – it is quite simply the infrastructure of modern financial services.
“AI is transforming fintech back-offices by automating routine processes and improving accuracy, while also enhancing customer support through faster, more consistent digital interactions, ultimately enabling firms to scale more efficiently without losing the human touch,” explains Shane Garahy, partner, risk consulting KPMG in Ireland.
The technology is improving customer experience. “AI is enabling a shift towards truly personalised finance, using real-time data to tailor products, insights and decisions to individual behaviours, helping customers manage money more effectively while building services that adapt as their needs change,” he explains.
It is also supporting fintech growth across risk, compliance and decision-making, “helping firms operate more securely, respond to emerging challenges in real time and innovate with confidence while maintaining strong governance and trust”, Garahy adds.
AI has become a critical tool in the fight against financial crime. “AI is helping fintech firms detect anomalies in real time, strengthen transaction monitoring, and identify emerging fraud patterns at scale while still relying on strong oversight and human judgment,” says Garahy.
The pace at which it is doing all this is accelerating.
In just a few years, GenAI has evolved into agentic AI that can not only answer questions, but also intelligently execute tasks.
“Traditionally, these types of tools have been focused on chat-type interfaces, but increasingly areas such as customer support have moved to voice and video interaction in a new type of agent called multimodal agents,” explains Martin Duffy, head of AI and emerging technologies at PwC Ireland.
“These are increasingly human in their look and feel, meaning that the opportunity for use in a customer support role is now becoming real.”
It enhances service overall. “It has long been the goal to develop and deliver personalised services to customers. With the advent of AI and agents there is now an opportunity to deliver hyper-personalised services to customers. Areas such as asset and wealth management are starting to focus on providing investment management services which traditionally were only available to high-net-worth clients. By using AI, they can provide these services to a wider set of retail clients,” Duffy explains.
Investment advice, customer access to guided research, and even agentic portfolio management are some of the capabilities at the core of these new services.
“Ultimately, AI is shaping a future where fintech is faster, more predictive, more personalised, and more resilient, but also one where firms must continue to demonstrate accountability for how decisions are made and risks are managed. Human judgment remains essential, particularly when results require internal escalation or regulatory review,” says Brian Fahey, chief executive of My Compliance Office, an Irish regtech company with a global customer base.
He believes that the technology firms that will be most successful long term in terms of AI are those that integrate it into their infrastructure and core controls, rather than treat it as a separate, standalone tool. “The competitive advantage is no longer simply adopting AI, but embedding it responsibly into day-to-day operations with the governance, transparency, and oversight regulators expect,” he adds.
In relation to risk scoring – the quantifying and prioritising of vulnerabilities, particularly in relation to cybersecurity – AI is improving the speed and accuracy of assessment by allowing firms to analyse larger and more diverse datasets in real time.
“This helps institutions identify behavioural patterns, emerging risks and anomalies that traditional models and point-in-time reviews may miss. That shift, from static review cycles to lifecycle-based monitoring, is where I see the most meaningful change taking place. AI can enable firms to implement a continuous assessment process that continuously updates risk based on customer profiles and related activities,” says Fahey.
“However, firms still need strong governance, explainability, and oversight to ensure risk models remain fair, transparent, and compliant with regulatory expectations.” In today’s business landscape, fraud detection and financial crime compliance is a strategic imperative, he points out.
“Ineffective controls can trigger enforcement actions, reputational damage, significant financial loss and operational disruption. Regulators and customers expect financial institutions to react instantly to bad actors and fraudulent transactions,” says Fahey.
“AI is significantly improving fraud detection by identifying suspicious activity patterns across transactions, communications, devices and behaviours much faster than manual review processes. AI models can enable firms to adapt to evolving fraud tactics quickly, which is increasingly important as financial crime becomes more sophisticated and digitally enabled.”
It’s also helping the compliance function to become more proactive and scalable in its surveillance, accelerating investigations and identifying emerging risks before they become regulatory issues. “The result is fewer human hours spent on low-value tasks and more focus on genuine areas of risk,” he adds.
But AI in itself comes with risk if it’s not implemented and managed responsibly.
“Financial institutions have long operated under compliance expectations centred on validation, documentation, and defensibility. When AI outputs influence compliance decisions, firms must be able to explain how they are supervised, audited and challenged,” explains Fahey.
“A key point to make here is that AI doesn’t change accountability. Firms still own every decision and every outcome. Regulators aren’t asking how advanced your AI is, they’re asking whether you can explain it, evidence it, and defend it. If you can’t show how decisions were made, who reviewed them, and what controls were in place, the technology becomes a risk in itself.”
