4 ways AI and open banking are driving a new wave of payments innovation
Open banking has transformed the financial landscape across the UK and Europe, driven by regulatory frameworks such as the Revised Payment Services Directive (PSD2). In the UK, adoption continues to grow, with over 11 million active users as of November 2024. As real-time account-to-account (Pay by Bank) payments gain traction, the convergence of artificial intelligence (AI) and open banking is unlocking even greater potential. AI’s ability to analyse financial data, detect fraud, and optimise payment processing is set to reshape the future of payments, offering businesses and consumers faster, safer, and more personalised payment experiences. This post explores how AI is shaping the next phase of open banking payments. 
1. AI’s role in fraud prevention
Security is paramount in payments, and AI is rapidly becoming an invaluable ally in fraud prevention for open banking. Modern AI systems can sift through transaction data in real time, detecting unusual patterns far more effectively than manual checks. For example, machine learning models learn what ‘normal’ behaviour looks like for users and swiftly flag anomalies - such as unusual high-value transfers, unfamiliar login attempts or repeat chargeback requests - for further review. These self-learning systems continuously adapt to emerging fraud tactics, allowing them to spot suspicious trends earlier and more accurately over time.
AI is also enabling a ‘zero trust’ approach to security. Practically, this means every payment request or data access attempt is continuously verified rather than assuming trust once a user is logged in. AI-driven tools constantly monitor interactions and look for subtle anomalies - such as changes in typing speed or unfamiliar device access - to spot threats that might otherwise go unnoticed.
Cybersource’s 2024 Global Fraud Report indicates a growing trend among merchants to adopt AI-powered fraud prevention tools. Businesses are increasingly using solutions like positive behaviour models, which identify typical customer behaviour and alert for anomalies, and negative behaviour scoring, which detects patterns linked with fraudulent transactions. These tools are being developed both internally and offered by 3rd parties.
2. AI-driven personalisation
One of the most exciting ways AI is influencing open banking is through highly personalised payment experiences. Financial services are moving away from one-size-fits-all, and AI is the engine making tailored experiences possible. In return for a user's consent, open banking APIs provide rich data on a customer’s spending habits, bills, and even gaming or shopping patterns, AI algorithms can offer insights and recommendations uniquely relevant to that individual. In fact, open banking providers are already using AI to tailor product recommendations and financial advice to each user’s behaviour and needs. This could mean, for example, a banking app proactively suggesting budgeting tips, a better savings rate based on your transaction history, or an eCommerce checkout that remembers a shopper’s preferred payment method and timing.
The combination of open banking and AI could essentially power a personal financial assistant for every user. As one industry executive noted, the magic lies in layering AI on top of open banking’s capabilities - that’s when truly individualised planning and guidance take off. Imagine an app that not only aggregates all your bank accounts via open banking, but also uses AI to analyse your spending and send useful nudges: ‘Hey, you’re close to your monthly grocery budget’ or ‘You can save on fees by paying this bill two days earlier’. Because these insights draw on the user’s actual financial data (with permission) and AI’s pattern recognition, they feel timely and relevant rather than generic. AI can even generate personalised dashboards highlighting what matters most to each user. Over time, this level of personalisation builds trust and engagement – users feel their financial service ‘gets’ them.
For fintech companies, iGaming platforms, or merchants, such tailored experiences can translate into higher customer satisfaction and loyalty. And importantly, all this is done with privacy in mind: open banking’s consent mechanisms let consumers control what data AI can use, ensuring personalisation doesn’t come at the expense of data security. It’s a win-win, giving users more value from their data while businesses better serve their customers’ unique needs.
3. Improving KYC and ID verification
Onboarding new users and complying with Know Your Customer (KYC) regulations can be a headache in finance – it’s traditionally paper-heavy, slow, and costly. AI is rapidly changing that by streamlining identity verification and compliance checks in the open banking world. A huge pain point has been the time it takes to verify identities; nearly half of banks globally have lost clients due to slow or clunky onboarding processes. AI aims to fix this through automation and smarter risk analysis. For instance, AI-driven document verification can confirm a customer’s ID in seconds by scanning passports or driver’s licenses, matching selfies to ID photos, and checking for forgeries – far faster than a manual review. Likewise, AI can instantly cross-check customer data against watchlists and databases to flag potential money laundering risks, accelerating Anti-Money Laundering (AML) compliance steps that once took days.
In an open banking environment, robust digital identity verification (IDV) is essential to ensure only the right people can access financial data and payment capabilities. Here, AI plays a crucial role. Modern IDV solutions now leverage AI and machine learning to detect anomalies and flag potential fraud based on user behaviour and device details. In practice, that might mean noticing if a device’s location or fingerprint doesn’t match the legitimate customer’s profile during account creation, and halting the process before fraudsters get in. AI-powered identity tools also help confirm that someone is who they claim to be throughout the account lifecycle – from the moment they sign up to each time they initiate a transaction. This is critical because fraudsters often try to open fake accounts or take over existing ones (for example, creating 'mule' accounts to funnel illicit funds). By catching synthetic identities or imposters with pattern recognition, AI prevents bad actors from ever entering the open banking ecosystem.
Crucially, AI makes these checks not only more secure but also smoother for genuine users. Instead of subjecting customers to endless forms and branch visits, fintech apps can use AI to verify identities in the background within moments. Biometric authentication (like facial recognition or voiceprint analysis) adds another layer of security with minimal friction – and AI ensures it’s accurate, matching faces to IDs even under varied lighting or spotting deepfake attempts. The result is a faster onboarding experience that doesn’t sacrifice compliance. Banks and payment providers can more easily meet stringent regulations (such as PSD2’s strong customer authentication rules) because AI is consistently checking identities and monitoring transactions for suspicious activity. Done right, this builds customer trust: people feel safer knowing the system will catch fraud, and they appreciate a quick sign-up flow. In short, AI is turning KYC from a bottleneck into a competitive advantage, helping open banking operators comply with rules while welcoming legitimate users with less hassle.
4. Enhancing transaction processing and decision-making
AI is also optimising the way payments are processed and authorised in open banking, making smarter decisions in split seconds. Traditionally, payment processing followed static rules – which could lead to unnecessary declines or delays if a transaction fell outside some predefined parameters. Now, AI-driven decision engines are adding more nuance. They analyse a wide range of data points around a transaction (amount, timing, past behaviour, device, etc.) to decide the best way to handle it. This means more legitimate payments get approved while suspicious ones are accurately filtered out. In eCommerce and iGaming, where failed payments or false fraud flags can cost revenue and increase churn, these AI refinements are game-changing. Case in point: machine learning models can adapt to seasonal shopping patterns and cross-border spending habits by examining behaviours across millions of consumers, rather than rigidly applying one-size-fits-all rules, as discussed in this AI in retail article by LeewayHertz. This flexibility helps reduce 'false declines' – where a real customer’s payment is wrongly rejected as fraud – a problem that can cost merchants more money than actual fraud. By understanding context (is the user on holiday? Is this purchase typical for them at this time of year?), AI can greenlight more genuine transactions and spare customers that annoying 'your payment was declined' moment.
Yaspa is also significantly invested in leveraging the power of AI to enhance transaction processing and decision-making. In 2024, we were awarded a UK government grant for our Intelligent Payments platform which leverages machine learning to monitor player transaction data and behaviour in real time to identify potential ‘markers of harm’. Applied specifically to the Safer Gambling use case, Yaspa will provide iGaming operators with access to player transaction data at the point of deposit, giving a significantly broader and more accurate picture of a player’s pan-operator activity. The application of AI modelling will then detect the likelihood of them being a ‘problem gambler’.
Another area where AI shines is payment routing and authorisation optimisation. When an open banking payment or bank transfer is initiated, there may be multiple paths or processors that can facilitate it – especially in a global context or when multiple banking partners are involved. AI systems can dynamically select the optimal route for each transaction in real time, maximising the chance of success. For example, if one banking channel is experiencing downtime or a particular acquirer has higher approval rates for certain cardholders, an AI-based platform can automatically route the payment through the best option within milliseconds. This intelligent orchestration was difficult to achieve with manual or rule-based systems, which couldn’t customise routing per transaction. Now it’s a reality: AI crunches historical and current data to predict which route will authorise the payment with the least friction and cost. The benefit to businesses is tangible – higher acceptance rates and fewer declined transactions. In fact, merchants using AI-driven payment routing have seen significant drops in transaction declines and an overall uplift in completed payments. Over time, AI can also learn from each failure, adjusting strategies to continually reduce payment errors.
Beyond routing, AI’s real-time data crunching offers better decision-making support in finance. Banks and fintechs deal with massive volumes of payment data, and AI is uniquely suited to process and analyse these large datasets for actionable insights, effectively aiding faster and smarter decisions. For instance, AI might detect that a user’s spending is trending upward and predict a potential overdraft, prompting a preventive alert or a credit top-up offer. Or for an online merchant, AI could analyse thousands of transactions to predict when during the day payments tend to spike or fail, allowing them to proactively allocate resources or adjust risk thresholds. These kinds of predictive insights help reduce hiccups (like payment declines due to insufficient funds or system loads) by addressing issues before they happen. In summary, AI is making the ‘plumbing’ of open banking payments more intelligent. Transactions flow more smoothly, legitimate payments face less friction, and both businesses and consumers experience fewer of those aggravating payment failures. It’s a smarter, more efficient payments pipeline, powered by AI in the background.
The future of AI in open banking payments
As we look ahead, the intertwining of AI and open banking is set to deepen, bringing both exciting opportunities and new considerations. One clear trend is the expansion of AI’s capabilities in payments beyond just prediction, toward content generation and richer interaction – the era of generative AI. We’re beginning to see AI chatbots and voice assistants that can initiate payments, answer finance questions, or even provide financial coaching. Imagine asking your smart speaker to pay your utility bill via open banking, and an AI securely handles the entire process through an open banking payments provider.
Another emerging trend is hyper-personalised finance. We’ve scratched the surface with tailored recommendations, but future AI might proactively manage aspects of finances for users. For example, an AI could automatically move money between accounts to prevent fees or optimise interest, based on rules you set. With the richer data coming as open banking grows into open finance (covering investments, insurance, etc.), AI could present a truly holistic view of one’s finances and make informed suggestions across all of it. Consumer loyalty apps, like Cheddar, are already using open banking data and AI to provide hyper-personalised offers and discounts to consumers based on their spending preferences. These advances could fundamentally change how consumers relate to financial services – it becomes more interactive, automated, and predictive. McKinsey estimates AI could contribute an astounding $2.6 to $4.4 trillion annually to the global economy across industries, and finance will grab a good slice of that. In open banking, we can expect AI to further improve fraud detection, deliver even more accurate analytics, and handle complex tasks like affordability checks with ease. Lenders might routinely use AI on open banking data to decide loan approvals in seconds, or merchants might rely on AI to gauge a customer’s risk level before offering pay-by-bank at checkout. The ecosystem of tools around open banking payments will likely include AI-driven services by default, from risk scoring to personal finance management.
However, the future isn’t without challenges. As AI takes on a bigger role in handling sensitive financial information, regulators are paying close attention. Ensuring AI is used ethically and transparently will be crucial. For instance, the U.S. Consumer Financial Protection Bureau (CFPB) has hinted at limits on using AI insights to manipulate consumer behaviour in open banking – a reminder that while personalised suggestions are great, they must serve the customer’s interest, not exploit it. In the EU, the upcoming AI Act will likely classify many financial AI systems (like credit scoring algorithms) as ‘high risk,’ meaning stricter oversight and requirements for explainability. And globally, data protection laws (GDPR and others) require that consumers’ data rights are respected even as we leverage that data for AI analysis. The good news is that open banking was built on a foundation of consent and security, which can extend to AI usage: consumers should be informed and in control of how their data and AI-driven profiles are used. Fintech companies and banks will need to collaborate with regulators to strike the right balance between innovation and privacy.
We also can’t ignore the practical considerations – 44% of merchants in one survey voiced concern about the complexity of integrating AI into their systems. To fully realise AI’s benefits, the industry will have to invest in talent, infrastructure, and clear strategies for deployment. Despite these hurdles, the trajectory is unmistakable: AI and open banking together are driving a new wave of financial innovation. We’re likely to see more partnerships between payment providers and AI firms, more regulatory clarity on AI’s do’s and don’ts, and continuous improvements in AI models as they train on larger open banking datasets. The end result could be an open banking payments ecosystem that is highly automated, intelligent, and inclusive – where transactions are frictionless, fraud is mostly preempted, and even small businesses or regulated sectors like iGaming can harness advanced AI tools via their open banking platforms without needing their own data science armies. It’s an exciting time on the horizon, with AI poised to unlock new possibilities in how we pay and manage money.
Conclusion
Open banking has already begun to reshape payments by breaking down data silos and empowering consumers with more choice. When combined with the power of AI, its impact is supercharged. AI brings to open banking payments enhanced security through smarter fraud detection, more personalised user experiences, quicker and safer onboarding, and streamlined payment processing that learns and adapts. For fintech professionals, iGaming operators, and eCommerce merchants, the message is clear: these technologies aren’t just buzzwords, but practical tools that can improve customer trust and boost the bottom line. Of course, embracing AI in open banking comes with responsibilities – ensuring compliance, protecting privacy, and keeping a human-centric approach. But done right, the convergence of AI and open banking promises a future of payments that is more efficient, intelligent, and user-friendly than ever before. In this new era, mundane payment pain points could become a thing of the past, and innovative financial experiences will be the norm. The journey is just beginning, and those who harness the synergy of AI and open banking will be at the forefront of the future of payments.
Yaspa is at the forefront of integrating AI and open banking, empowering businesses with smarter, safer, and more seamless payment solutions. For iGaming operators, by combining the predictive power of artificial intelligence with the real-time insights provided by open banking data, Our Intelligent Payments solution uses advanced AI-driven analytics to proactively identify vulnerable players by continuously monitoring affordability, spending patterns, and behavioural trends. This intelligent approach not only helps operators effortlessly comply with responsible gambling obligations but also fosters trust and builds lasting customer loyalty by creating a safer, more transparent gaming environment.
Watch our recent webinar hosted by Yaspa’s Head of Product Max Collinge, about how AI is helping to enable safer gambling.
Get in touch with us today to learn how Yaspa can implement smarter, faster and more intelligent payment solutions for your business.
