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Finextra
4 days ago
- Business
- Finextra
Top 5 Mobile Banking Trends for 2025: By Viacheslav Kostin
Mobile banking is reshaping the financial services industry, driven by technological advancements and evolving user expectations. In 2025, banking apps will deliver smarter, more secure, and integrated experiences. What's driving this transformation? Based on industry research and expert insights, here are five pivotal trends redefining mobile banking. AI-Powered Personalisation How Does AI Elevate User Experience? Artificial intelligence is transforming banking apps into intuitive financial tools. According to Gartner, global AI software spending is projected to reach £241 billion by 2025, with banking leading adoption. AI analyses user data to provide tailored insights, automating routine tasks. Key features include: Real-time chatbots handle 85% of customer queries instantly, per Juniper Research. Personalised budgeting tools based on spending habits. Fraud detection systems, reducing false positives by 50%, as reported by Accenture. These capabilities make banking apps feel like personal advisors, enhancing user engagement and financial decision-making. We demonstrated this in a 700,000-user mobile banking app case , where AI‑driven personalisation significantly improved user satisfaction. Advanced Biometric Security What Ensures App Security? With cyber threats surging, global losses from cybercrime reached £6.3 trillion in 2024, according to Cybersecurity Ventures, banking apps are adopting robust protections. Biometric authentication, like fingerprint and facial recognition, is now standard, with 78% of banking apps implementing it, according to Statista. Emerging security measures include: Multi-factor authentication, combining biometrics with one-time codes. Behavioural biometrics, which tracks user patterns, is adopted by 60% of banks, according to Forrester. Zero-trust architecture, with 86% of firms initiating adoption, as per Cisco's 2024 survey. These advancements ensure secure transactions, building user trust. How safe is your banking app today? Embedded Finance Integration Why Is Embedded Finance Booming? Embedded finance integrates banking services into non-financial platforms, such as e-commerce or ride-sharing apps. A 2024 Bain & Company report predicts the global embedded finance market will reach £550 billion by 2026. Benefits include: Instant financing at checkout, boosting conversion rates by 30%, per McKinsey. Seamless financial tools within user-favourite platforms. API-driven integrations, with 70% of retailers adopting them, per PwC. This trend enhances convenience and business growth. Could embedded finance transform your daily transactions? Blockchain and Decentralised Finance How Does Blockchain Enhance Transactions? Blockchain and decentralised finance (DeFi) enable secure, intermediary-free transactions. By 2025, 25% of banking apps will incorporate blockchain features, per Deloitte. With global blockchain spending forecast at £15 billion, per IDC, key advantages include: Smart contracts, settling transactions in seconds. Tamper-proof records, reducing fraud by 80%, per IBM. Instant cross-border payments, cutting costs by 40%, per Ripple. Blockchain empowers users with control and efficiency. Will it redefine your financial operations? Open Banking for Enhanced Insights Why Is Open Banking Critical? Open banking, enabled by secure APIs, connects financial accounts to third-party services. By 2025, 65% of European banks will fully adopt open banking, per Capgemini. This trend offers: Unified financial dashboards, used by 40% of consumers, per Plaid. Real-time loan approvals, speeding up processes by 70%, per EY. Personalised budgeting tools, improving savings for 55% of users, per Accenture. Open banking puts users in control. How could it simplify your financial management? The Future of Mobile Banking In 2025, banking apps will combine AI-driven personalisation, zero-trust security, and seamless integrations to meet user needs. Gartner predicts 70% of enterprises will adopt industry-specific cloud platforms by 2027, enhancing banking innovation. These trends, backed by robust research, highlight a shift toward secure, user-centric financial solutions. But that's not all - explore the WislaCode Solutions blog for a wealth of resources, including industry news, thought leadership, and actionable tips to help you navigate the ever-evolving world of financial technology.
Finextra
12-06-2025
- Business
- Finextra
AI in fintech: Transforming customer experience and operational efficiency
0 This content is contributed or sourced from third parties but has been subject to Finextra editorial review. Why AI—and why now? After two years of explosive progress in generative models, artificial intelligence (AI) has become the defining force behind innovation within financial services. According to NTT Data, a remarkable 91% of banking boards now have generative AI (Gen AI) initiatives on their agendas - a level of executive sponsorship unmatched by any other technology wave in decades. The benefits of AI in banking are two-fold: sharper, more human-centred customer experiences, and radically leaner operations. 1. Re-imagining the customer experience 24/7, human-grade service From the basic FAQ widgets of the past, banking chatbots have matured to the sophisticated, conversational advisors in use today. This technology can execute transactions and escalate complex cases, saving institutions an estimated US $7.3 billion in annual service costs, according to Juniper Research, and freeing up resources that banks can redeploy to higher-value client work. Large-language-model agents already handle document queries and policy explanations at near-human levels of comprehension; research prototypes such as the CAPRAG hybrid RAG pipeline show how banks can blend different data (vector and graph) retrieval methods for even deeper context. Hyper-personalisation at scale Machine-learning algorithms continuously analyse individuals' spending patterns, lifestyle signals and financial goal trajectories to determine 'next-best actions'. Recent studies on AI-based personalisation have revealed impressive prediction accuracy above 88 % for recommending credit-risk-aware products. In open-banking markets, the scope of these insights is widening. By aggregating data from multiple accounts, banks can enable richer, self-driven ways of managing money, such as automated bill-splitting, just-in-time savings sweeps and tax-loss harvesting, long before the consumer even makes a request. 2. Quiet revolutions in the back office Document and contract intelligence JPMorgan's COIN platform parses commercial loan agreements in a matter of seconds - work that previously took lawyers an estimated 360,000 hours a year. Similar natural-language models now generate regulatory reports, reconcile payments and draft marketing copy —slashing turnaround times from days to minutes. Real-time risk and fraud controls Seven in ten financial institutions already lean on AI to police faster-payments fraud and synthetic ID schemes, often using third-party platforms that monitor billions of signals in the cloud. Even financial regulators are adopting these tools - Germany's BaFin reported that AI added to its market-abuse alert system last year has 'substantially improved hit rates', raising the odds of catching offenders. 3. Governance and ethics: holding the trust line As models move deeper into functions such as credit approvals, portfolio advice and surveillance, then bias, explainability, and privacy become existential. The forthcoming EU AI Act will designate many financial-risk models as 'high-risk', meaning they will require rigorous documentation, fairness testing and human-override channels before the 2026 enforcement date. Firms that embed model cards, counterfactual explanations and privacy-preserving learning methods such as federated or synthetic-data pipelines into their development lifecycle will be in a stronger position for global compliance. 4. What comes next? A look to the future Agentic finance (2025-2027) - Expect 'level-3' autonomous finance — systems that automatically move idle cash to best performing accounts, refinance debt when interest rates dip and negotiate utility contracts. Frameworks outlining the six levels of autonomous finance suggest mainstream adoption of self-driving money within 24 months. Embedded AI and open finance - Secure APIs are dramatically shortening the distance between data, model and moment. Early results from Citizens Bank's open-banking platform show a 95 % drop in traditional screen-scraping incidents and pave the way for real-time credit scoring via external apps . Edge and on-device LLMs for privacy - As compute footprints shrink, 'small' frontier models will run directly on mobile secure enclaves. This will keep biometric spending signatures local while still supporting federated learning updates to the cloud. Continuous assurance tooling - Expect AI-for-AI: dedicated validation models that watch production systems for drift, hallucination and unfair impact. Regulators are likely to mandate such controls as a condition for using GenAI in regulated financial advice. Human-in-the-loop evolution - The most successful fintechs will treat AI as a teammate, not a replacement. Roles will shift from rote processing to model stewardship. This will entail curating data, auditing outputs and designing empathetic intervention pathways — a skillset already highlighted by BaFin's experience and echoed in global surveys of bank leadership). AI is no longer a laboratory curiosity; it has become the new operating system of finance. Institutions that harness its power responsibly — balancing radical automation with transparent oversight — will define the next era of customer trust and operational excellence. At the Gillmore Centre, our research agenda centres on these twin pillars: unlocking AI's generative potential while engineering the guardrails to ensure finance remains fair, explainable, and human-centric. The next 18 months will separate early experimenters from AI-native leaders; the next five years will decide the competitive map of global financial services. The time to scale, audit and govern is now. The Gillmore Centre series features authors from the Gillmore Centre of Financial Technology at Warwick Business School as they explore new innovations in fintech from an academic perspective. Keep an eye out for more articles from the Gilmore Centre to learn more about new developments in the field.
Business Wire
03-06-2025
- Business
- Business Wire
payabl. launches Virtual Business Cards to empower smarter business spending
LONDON & AMSTERDAM--(BUSINESS WIRE)--Leading European financial technology provider, payabl. has launched its Virtual Business Cards service, a digital payment solution designed to give businesses greater control, security, and visibility over their spending. "With the launch of our virtual cards service, we're making it easier for companies to take greater control of their payments." Share Virtual cards are a digital alternative to physical credit or debit cards, offering real-time issuance, customisable limits, and transparent spending to streamline expense management and enhance financial oversight. Businesses can generate cards instantly, assign them to team members, set spending limits, and freeze/unfreeze access when needed. Built to simplify B2B payments, payabl.'s Virtual Business Cards are ideal for e-commerce companies needing extra transaction security, start-ups and scale-ups managing supplier budgets and global teams with travel and multi-currency expenses. The new proposition further strengthens payabl.'s Business Accounts offering and underpins the company's commitment to helping businesses stay ahead in today's rapidly evolving payments landscape. Ugne Buraciene, Group CEO of payabl., said: 'With the launch of our virtual cards service, we're making it easier for companies to take greater control of their payments. From improved oversight of spending, to the ability to set budgets and ensure the highest level of security, payabl. is removing the friction from payments so businesses can focus on what really matters: growing their businesses and better serving their customers and partners.' payabl.'s virtual cards service has been designed specifically to meet growing merchant demand and usage, with the total volume of virtual card transactions expected to reach 175 billion by 2028, rising from 36 billion in 2023*. The value that virtual cards bring to businesses is evident, with 94% of firms that use them saying their transactions are faster, more detailed, and more secure**. Breno Oliveira, Head of Product at payabl., added: "The virtual cards market is booming, with transactions now in the billions and set to rise significantly. While much focus has been on consumer use cases, the value they can bring to businesses in cutting admin time spent on payments and boosting productivity is evident. And at payabl., we're unlocking those benefits for more businesses.' Card issuance now sits alongside payabl.'s wide range of payment solutions, including card acquiring, local payment methods, and point-of-sale (POS) terminals. Its Business Accounts enable customers to send, receive, and manage multi-currency payments 24/7/365, with access to an all-in-one dashboard and dedicated client relationship managers. Notes to editors Find out more about payabl.'s business accounts: *Virtual Cards Market Statistics 2023-2028, Juniper Research: About payabl. Established in 2011, payabl. is a leading financial technology provider with offices in Germany, the Netherlands, Cyprus, and the UK. The company offers a comprehensive range of payment products, including card acquiring, business accounts, integration to over 300 local payment methods, and POS terminals. payabl. offers its customers a high-tech, high-touch approach, providing future-proofed payment solutions to merchants from a wide range of sectors around the world. With unrivalled experience in helping clients navigate the complexity of an ever-evolving payments environment, payabl. is the trusted partner for the world's most innovative merchants to unlock growth. To learn more, visit:
Forbes
28-05-2025
- Business
- Forbes
The Transaction That Never Happened: How Fraud Stifles Our Economy
Hacker and laptop made of binary code. Ones and zeros. With copy space. Across industries, economies, and every digital touchpoint in between, fraud is quietly compounding costs, not just by stealing money, but by stopping legitimate transactions before they even happen. While fraud attempts make headlines when a heist lands, there's a much more insidious problem right under the surface: the transaction that never happened because of our attempts to stop fraud before it happens. These are the losses you can't always see in your quarterly report: the customers you turned away because your system flagged them as risky, the potential revenue you missed by setting your fraud filters too tight, and the businesses that slowly destroy the trust between themselves and their consumers because a few bad actors shaped how they treat everyone. And it's only getting worse. Fraud is now multimodal. It doesn't show up just as stolen credit cards or phishing emails like it used to. Today, fraud arrives through fake IDs, deepfaked voices, spoofed IP addresses, social engineering over messaging apps, and increasingly, through AI-generated personas that can pass casual scrutiny Any app, voice, or face can be weaponized through any channel imaginable. According to recent estimates from Juniper Research, merchants are projected to lose over $362 billion globally to online payment fraud between 2023 and 2028. Meanwhile, the systems designed to catch this fraud are often blocking legitimate transactions as well with false positives routinely outnumbering actual fraud. The question that beckons an answer is simple, with answers that have deep roots: how do you protect your customers without treating them like suspects? 'Fraud doesn't just take the money in your account,' says Forter CEO and co-founder Michael Reitblat. 'It takes the trust in your system. And in trying to protect against it, too many companies go too far. They build walls so high that even their best customers can't climb over them.' He would know. Reitblat co-founded Forter with the belief that the future of fraud prevention shouldn't be focused solely on tightening the filters, but applying them smarter. That means knowing your customers deeply enough to recognize them when they show up, even if their device, location, or behavior looks slightly different than last time. 'We need to start by flipping the mental model companies approach fraud with,' Michael begins. 'Instead of assuming guilt and proving innocence, we should assume the customer is legitimate and be fast and smart enough to catch when they're not.' The reason why we don't see this approach being the norm is that it requires data, huge volumes of it, and systems that can learn over time. Forter's platform, for example, sits on top of a global network of merchants, letting it see patterns no single merchant could identify on their own. It's a distributed immune system for the digital economy. Much of the tech that modern fraud-detection relies on wasn't available just a few short years ago, and the industry is evolving faster than ever. While the tech is a key drive, Michael argues that the key to handling fraud better lies within consumer and vendor psychology. Simply put, we need to reframe what success in fraud prevention looks like. 'Everyone measures fraud prevented. But what about sales saved?' he asks. 'If your system blocks 99% of fraud but also turns away 10% of good customers, that's not success. That's loss. And it's often invisible, as is the lack of trust that underpins it all.' Zoom out from payments, and the same principles of trust apply across cybersecurity. Gil Geron, co-founder and CEO of Orca Security, has spent years helping companies secure their cloud environments. But for him, the real challenge is psychological as much as it is technological. 'Too much of cybersecurity is built around fear,' Geron says. 'Fear of breaches, fear of compliance issues. But when you lead with fear, you create friction. You slow down developers, frustrate employees, and erode trust internally.' The new wave of cybersecurity professionals often argue that when everything is cloud-first and developer-led, security can't be a blockade, it has to be a partner. Geron agrees and notes that the best security is invisible: it runs in the background, integrates seamlessly, and empowers teams rather than policing them. 'What we need is secure velocity,' he explains. 'Move fast, but safely. Don't just scan the environment once a month, understand what's happening in real time, with context. This way we ladder up to trust organically, and remove the sources of friction that keep good actors from transacting on the platforms they want.' The idea of context over details is a critical one. In fact, it can be transformative when weaponized on behalf of the consumer. Whether you're approving a payment or flagging a risky container in the cloud, the system needs to know what normal looks like in order to detect what's not. That requires machine learning, behavioral baselines, and yes, trust in your users who sometimes order flights to Aruba at 2am right after rejoining Netflix and ordering take-out from a Nepalese restaurant for the first time with the same credit card. 'Security isn't about saying no as the default,' Geron says. 'It's about having the necessary trust to say yes to the right people, in the right way, at the right time.' Thomas Brunner, CEO of Gigapay, sees the consequences of broken trust up close. His platform helps creators and freelancers get paid across borders. But in a world where fraudsters can fake identities and automate scams, the burden of trust has never been higher. 'In the creator economy, you don't have time to run a KYC check manually or hold payments for weeks,' Brunner explains. 'If you don't trust the user instantly, the whole model falls apart.' Gigapay uses a mix of real-time risk scoring and user behavior analysis to spot anomalies. But the key, Brunner says, is not punishing everyone for the mistakes of a few. 'Fraud is the exception, not the rule,' he says. 'If we design our systems assuming everyone is trying to cheat, we break the experience for the 99% who are just trying to earn a living.' The stakes are especially high in the gig economy, where payouts can make or break someone's rent. A missed transaction is a data point of deep actuarial interest for sure, but it's much more than that for those who it impacts. In fact, it's often a livelihood. 'Trust is the platform,' Brunner says. 'Without it, the economy doesn't move.' Sometimes, the block comes from a lack of trust in the tools we use themselves. Brooke Hartley Moy, CEO of Infactory, is building an AI insights engine designed for enterprises. Her platform helps companies find answers they can trust, pulling not just from the open web, but from verified datasets and curated sources. 'We make billion-dollar decisions based on AI,' Moy says. 'But the foundation of that AI is often unclear. Where did this answer come from? Who vetted it? Can I trust it?' That uncertainty, she argues, is its own form of friction. Friction we should work hard to minimize. Companies hesitate to deploy AI not because it doesn't work, but because they don't know when it will, or whether it might do something entirely different than tasked. 'Accuracy can't be an afterthought,' Moy explains. 'Having trust in your tools and the answers they give you is the difference between action and paralysis. If you can't trust the output, you won't move forward. And that's another kind of transaction that never happens.' For her, solving this trust gap is about structure and standards. We start with what the AI says, and we trust it based on how transparently and reliably it says it. 'The future of decision-making requires not just intelligence,' Moy adds. 'It requires provenance.' At Nightwing, an intelligence solutions company spun out of RTX, Chief Technology and Data Officer Chris Jones is thinking of fraud, trust and everything above on a bigger scale. His job is to figure out how to protect critical systems, not just from fraud, but from coordinated attacks on the scale of the digital infrastructure of entire countries. 'There isn't a more poignant set of threat vectors than the ones we're seeing now,' Jones says. 'And it's not just about stopping bad actors. It's about making sure the good ones can still operate.' He sees a future where cyber offense and defense break through their silos and blossom into strategic complements that build the foundations for trust across the entire economy. 'We've been playing defense for years,' he notes. 'But if we want to maintain a global digital order, we have to think about sustainability, resilience, and sometimes, deterrence.' In other words: just like in commerce, the real cost of a breach isn't just what's stolen. It's what's prevented. In the end, friction grinds the strongest of gears down to a halt. If attacks deter innovation, stifle engagement, or shake public confidence, they succeed without breaching a single firewall. 'The blue team can win,' Jones says. 'But we have to scale them faster than the red team evolves. That means tools, talent, and trust. It means reducing friction for the people doing the right thing.' Fraud captures our attention and it is easy to over-index on it just because of how often it is the signal that breaks through the noise. But its most dangerous form is quiet. It hides in checkout forms that never get filled, apps that go unopened, accounts that never activate. It sits in the unseen shadows of the economy. The almost-purchases, the never-hires, the frozen budgets and the client who never returns. Preventing this form of friction is first and foremost a design challenge. Those who want to surmount this challenge need to build systems that can treat trust as the default instead of the reward for perfect compliance. In the end, what drives growth isn't just the blue team's defense or a tighter fraud-filter. Instead, it's a firm belief that the system will work as intended. That the transaction will go through. That the other side is who they say they are. And when that belief is protected, the economy doesn't just survive. It thrives.
Entrepreneur
19-05-2025
- Business
- Entrepreneur
How to Protect Your Business From Deepfake Fraud
Proactively protect your brand with a strategy that adapts to new threats and legal standards. Opinions expressed by Entrepreneur contributors are their own. In January 2024, a finance director at a UK firm transferred $25 million to fraudsters after a video call with what appeared to be the company's CFO — a very sophisticated deepfake. This incident is far from isolated. The global losses projected due to ecommerce fraud surged from US$44 billion in 2024 to $107 billion in 2029; a massive 141% increase, according to a report from Juniper Research. Compounding the problem, a staggering 60% of consumers now doubt the authenticity of online content, citing concerns over AI-generated misinformation, deepfakes and content overload, as revealed in Accenture's Life Trends 2025 report survey. For entrepreneurs and business leaders, the threats are twofold: reputational damage from deceptive synthetic media and legal liability as governments worldwide enact stringent AI disclosure laws. Current solutions like watermarking and AI detection tools are reactive by nature. Watermarking can be easily removed or forged, while AI detectors fail to identify manipulated content by nearly 30%, according to University of Pennsylvania researchers, by simple tweaks like added whitespace or typos. Legal actions, meanwhile, often come too late to mitigate damage. Thankfully, a solution exists: blockchain + AI-powered digital twins. Related: Hackers Targeted a $12 Billion Cybersecurity Company With a Deepfake of Its CEO. Here's Why Small Details Made It Unsuccessful. The rise of digital twins Digital twins or avatars are a bridge between the physical and digital world, helping optimize systems and personalize our day-to-day experiences (travel, work, shop, healthcare system and beyond). By embedding AI avatars with NFT passports, which act as tamper-proof digital certificates stored on the blockchain, these IDs create a verifiable record of an avatar's origin and any subsequent modifications — ensuring entrepreneurs and businesses can verify authenticity at source rather than scrambling to detect fakes after the fact. Consumer trust is inextricably linked to transparency. A 2024 Edelman report found that 62% of consumers only trust AI-generated content if its provenance can be verified. Blockchain-based authentication addresses this demand head-on. There is a growing trend of integrating NFT-based digital passports across various industries to enhance product authenticity, traceability and customer engagement. The corporate world is already adopting this approach. For instance, Breitling, a Swiss luxury watchmaker, partnered with Arianee to provide each watch with a blockchain-based digital passport. Since then, there have been over 200,000 NFTs created, with approximately 30% customer adoption. In the Art & Collectibles industry, Arteïa launched its Arteïa Connect, a secure digital passport for artworks anchored on the blockchain and securely linked to the piece via encrypted NFC tags, ensuring authenticity and provenance. Even the healthcare industry is adopting similar frameworks. The UK NHS's Digital Staff Passport uses blockchain to authenticate medical professionals, while Mayo Clinic partnered with Safe Health Systems to deploy AI-powered provider IDs for telehealth — critical steps to combat impersonation scams. By certifying authenticity at the point of creation, businesses are thus fostering trust while mitigating the risk of reputational damage. Related: Blockchain, NFTs and the New Standard for Identity and Security Navigating the AI wave For entrepreneurs, navigating the AI landscape requires a proactive approach. First, recognize that public-facing figures are prime targets for deepfake manipulation. Regular monitoring for fraudulent content is essential. Second, anchor digital identities to verifiable technologies like blockchain. Third, staying ahead of regulatory shifts is equally critical. The EU AI Act, the world's first comprehensive AI law set to take effect this year, imposes fines of up to 7% of global revenue for undisclosed synthetic media. Similar measures are emerging worldwide, from the US Deepfake Act to India's draft deepfake penalties, signaling a global trend toward stricter oversight. Regulators want proof, not promises. The blockchain's immutable audit trails provide exactly that. And, finally, treat digital identity protection with the same rigor as cybersecurity. Assign accountability within your team, conduct regular audits of AI tools, and consider partnerships with insurers specializing in deepfake liability. The future path is clear: Deepfake fraud is no longer a hypothetical threat but a present-day liability. While detection tools play an important role, blockchain-based authentication offers a proactive defense mechanism. Just like SSL certificates secure ecommerce, NFT passports can do the same for AI by securing identity and authenticity. For entrepreneurs and businesses, the choice is clear: to build trust through verification now, or risk losing everything to a synthetic scam tomorrow. In the rapidly advancing age of AI, authenticity won't just be important, it will be the foundation of trust and competitive advantage.
