Latest news with #fintech
Finextra
an hour ago
- Business
- Finextra
Inside AI Assisted Software Development and why tools are not enough (Part 1): By John Adam
The recent squeeze on funding and margins is by no means only being felt in the financial services and fintech sectors. But it's fair to say the pinch is particularly hard and the necessity to quickly and effectively innovate is simultaneously more pressing than ever. The good news is, new AI tools can speed up delivery and improve the quality of software projects without adding to headcount. But even if that general statement is true, just using tools is not enough. Especially in a regulated industry like financial services. If there is no pre-approved list of tools and how and where they are applied in an SDLC (software development lifecycle), organisations have governance, observability, measurability and consistency issues. If 'real' gains are not measured by benchmarking against 'before', do they really exist? Tree falling in a forest metaphor. Certainly not in a way that can be scaled across or up an organisation. There is no clear business case, just intuition. Are tools and where and how they are being used compliant with organisational policy and regulatory frameworks? Has anyone read the privacy policies? I'm personally convinced that a big AI company having its Facebook/Cambridge Analytica moment falls under 'when, not if'. And when the first big AI privacy scandal does break, you don't want your organisation published in a list in a newspaper. To benefit from and scale the gains of an AI-assisted SDLC, organisations need a framework for structured, consistent integration + governance, observability and measurability. Just tools isn't enough. Realistic gains from an AI-assisted SDLC It's important to note that at the time of writing, we are in a period of rapid change in AI tooling. A good framework operates at a level or two higher than specific tools and allows for them to be interchangeable with upgrades. The market most of us operate in is at a point in its cycle where resources are at a premium. Most of the organisations I work with are expected to deliver more with less compared with pre-2023. In that context, banking the productivity gains achievable with AI tooling is non-negotiable. Organisations are demanding it in the demand for greater, better output despite fewer resources. Getting it right is also non-negotiable and that means marrying increased productivity with measurability, observability and governance, which I cover in-depth in Part 2 of this article. As an introduction to building a proper framework, I'll start by explaining the realistic improvements AI can provide to each stage of the SDLC: Product prototyping Developers use prototypes to test idea viability and functionality, and to gather user and investor feedback. Historically, the average prototype required 2 to 6 weeks of teamwork to complete. But by amplifying developers' work via low-code/no-code prototyping and AI-generated code and other AI tools, a clickable prototype can now be completed in days or even hours. UX/UI design UX (user experience) and UI (user interface) designers collaborate closely with developers to design website and app interfaces. Using AI tools that can quickly generate multiple design mock-ups and UI components based on foundational style guides and example concepts, designers can visualise ideas and user flows in various contexts to improve design clarity and direction long before designs touch a developer's desktop. Clarity improves the quality of initial designs and reduces designer-developer back-and-forth, meaning larger projects that took 4 to 6 months to complete now require far less effort and time. Even UXR (User Experience Research) is accelerated and refined. User interviews are, by necessity, long and complex, and result in large, qualitative datasets. AI tools can highlight patterns and repetition in datasets and transcripts in seconds—shining a spotlight on insights, false positives or even biased questions that human researchers may have overlooked. Architecture Software architects plan higher-level design, bridging technical and business requirements. Their diagrams include the sum of a products' components and their respective interactions; until recently, the initial design phase alone took 1 to 2 weeks. Using AI, architects can quickly draw up diagrams to easily visualise these relationships and standardise dependency versions across services. AI can also be trained to use PR comments to report architectural violations, and libraries can be unified to encourage stability across features. Better consistency and immediate feedback mean architects can work faster and create fewer iterations of a product before diagrams meet stakeholder expectations. Coding AI-powered tools for coding have a variety of use cases. My team uses a mix of tools and GenAI to: ensure comprehensive project documentation, automate code documentation and README generation, scan for duplicate code and suggest improvements, improve understanding of complex, inconsistent or unfamiliar code bases, unify code styles and standards across different microservices, and perform code completion and check for bugs and inconsistencies based on defined standards. Paired with manual oversight to catch any mistakes, we've accelerated writing and testing code by a minimum of 20% across projects. GenAI makes complex codebases easily understandable—meaning team members can flexibly move to work on unfamiliar projects and diminish time spent on internal comms by about 25%. One tool we use is SonarQube, which reviews code without executing it. It runs automatically in GitLab CI/CD (Continuous Integration/Continuous Delivery and Deployment) pipeline to find bugs, report security vulnerabilities, and enforce code standards to unify style and mitigate potential misunderstandings down the line with better code readability. Testing and QA (Quality Assurance) As they write code, developers write and run unit tests to detect initial bugs and security issues that eat up between 10% and 20% of their time. The SDLC is slowed further by code reviews and PRs, or feedback from experienced colleagues. Tests are postponed by days, sometimes weeks, if various code reviews are required and dependent on busy colleagues. GenAI can augment developers' efforts by writing unit tests, conducting code reviews and PRs in real time, and automatically generating and solving for edge cases to overcome bottlenecks like a lack of expertise or teammates' availability. AI augmented QA can reduce redundancy, unify access to code, and consolidate fragmented knowledge across a project to make a QA team more efficient. And AI-driven tools like Selenium, for example, can automate web app test writing and execution, accelerating product releases and improving product reliability. Automated testing is especially compelling in the context of projects with tight deadlines and few resources. For example, my team's AI toolkit for QA testing includes Llama 3.3 LLM to generate test cases and analyse code and Excel-based legacy documents, IntelliJ AI Assistant to automatically standardise test case formatting, and GitLab to run and test scripts automatically in the CI/CD pipeline. QA is one of the most impactful applications of AI tools in the SDLC and can commonly slash the resources required by up to 60%, while increasing test coverage. Deployment When a product is deployed to end users, AI can be added to the CI/CD to forecast use patterns and improve caching strategies, as well as automatically prioritise and schedule tasks for parallel execution. With AI oversight, the number of repetitive tasks is automatically reduced and resource allocation anticipated, improving latency and product release cycles without added manual effort. And AI-driven caching accelerates and simplifies rollbacks (reverting a newly deployed system to a more stable version of itself) by analysing previous deployments and predicting the necessary steps, reducing further manual effort by DevOps teams, for instance. My team uses Dytrance during deployment, which monitors and analyses system status, and sends self-healing recommendations in real time. Maintenance and Monitoring At this stage, teams work to fix bugs, keep the system secure and functioning well, and make improvements based on user feedback, performance data and unmet user needs. AI can automatically perform root cause analysis for error monitoring, and suggest solutions for maintenance and debugging. Tools my team uses include AWS Cloud Watch and Azure Monitor with AIOps, which automatically collect, analyse, and suggest responses based on monitoring data, accelerating issue response and system updates by 10x. The big picture The acceleration of the individual stages of software development is incentive enough for some teams to add tools and GenAI models to their workflows; especially at stages like QA and coding, where use cases are various and results potent. But by taking a step back and considering AI's impacts on the SDLC holistically, the argument in favour of AI implementation can be turned into a real business case. A business case that can be used to accelerate AI transformation across an organisation: Backed by a strong framework, organisations implementing AI across their SDLC see a 30%+ acceleration across projects in the first 6 months. The keyword being 'strong.' Organisations need a framework that guides leadership to select tools and govern their use, measures outcomes to understand the amount of value different tools offer, and encourages adoption in teams' workflows. Without it, teams are unable to measurably extract the full potential from new tools and efforts, and risk breaching internal and third-party governance in areas such as data privacy. Keeping my word count and your patience in mind, I split my deep dive into a framework for AI governance, measurement and adoption into a separate article: Here is Inside an AI-assisted software development framework: using tools is not enough Part 2.
Finextra
5 hours ago
- Business
- Finextra
Speak Without Words: By Imanuel Kaiser
You can tell in seconds, some fintech products click. Why? They look good, feel considered, give a sense of control. What you're seeing is design doing the heavy lifting. To their detriment, most startups don't treat design like a real business lever. Instead, they might think of it as a coat of paint to add once the product works. But great fintech products aren't painted. They're designed and built from the inside out. Every front-end element: spacing, animation, colour, copy, tone, works to build utility and inspires emotional confidence. That confidence is what keeps users moving, trusting, and coming back. Design decisions are business decisions. Ignore them, and you leave money on the table. Fintechs should feel like music software A great strategy would be to borrow from apps like Apple Music and Spotify, not in terms of features, but in feel. Those apps are highly emotional products. They're tuned to human behaviour and express personality. That idea matters in fintech more than people admit. Personal finance can be stressful and many people don't enjoy thinking about it. So if you can create a space that feels intuitive, confident and a little bit joyful, you're going to get ahead. That's why the best fintechs don't look like banks, they're starting to look more like lifestyle apps you want to spend time in. Design-first fintechs are surging ahead Design features are a forever imprint in the product and scale in ways most marketing doesn't. The strongest consumer fintechs right now such as Revolut, N26 and Wise, have product teams that prioritise design because it drives growth. They know that if you can make financial tools feel light, modern and emotionally fluent, you gain a level of customer engagement traditional players can't touch. You also spend less on support, churn less, and get more referrals. Earning trust Trust isn't won by saying 'trust me' or showing a padlock icon. You win it when the experience feels like it should. That means a responsive UI. Examples might be a transfer button that animates with just the right delay, or typography that's readable without effort. Don't design by committee Finally, if your sign-up form looks like a compliance department built it, it probably was. Most legacy banks ship features. Great fintechs ship experiences. That starts with a small team that cares obsessively about how each part of the product feels, not just what it does. I'd go as far as saying: if your founding team doesn't include someone with a strong design eye, or you're not bringing in that instinct early, you're at a disadvantage. It will show. And no amount of after-the-fact polish will fix it. In conclusion Most users won't say why they don't like your app. They won't complain about the copywriting or the dropdown spacing, they'll bounce. Teams who invest in emotional design, who make things feel smart, fast, easy, and respectful will get a different outcome. Their users are proud to recommend them. And they win market share not by shouting louder, but by being better. When your product has great design, you start to speak without words, and that's when users really start to listen.
Yahoo
8 hours ago
- Business
- Yahoo
Elon Musk Just Turned X Into Wall Street's Newest Rival -- And It's Just the Beginning
X, the platform formerly known as Twitter, is inching closer to becoming a full-blown fintech ecosystem. CEO Linda Yaccarino told the Financial Times that users will soon be able to invest or trade directly on the apppart of Elon Musk's grander vision to turn X into a U.S. version of China's WeChat. That includes everything from peer-to-peer payments via X Money to digital tipping and possibly even credit or debit cards, which could arrive as early as this year. The rollout will begin in the U.S., with Visa onboard as a launch partner, before expanding to other markets. The move comes as X tries to climb out of its post-acquisition slump. Since Musk's $44 billion takeover, advertising revenue has dropped sharply, and the platform has battled both reputational damage and advertiser boycotts. Yaccarino says 96% of pre-acquisition advertisers have returned and expects revenue to rebound to 2022 levels super soon. But not everyone's convinced. Some advertisers remain wary, citing concerns over brand safety, content toxicity, and reports of pressure to spend or face legal action. Research firm Emarketer sees X's 2025 revenue reaching $2.3 billion, up from $1.9 billion last yearbut still far below the $4.1 billion it generated when Musk first took the reins. There's also a tech twist. In March, Musk folded X into his AI startup xAI in a $45 billion deal. Yaccarino believes this will double the engineering horsepower behind the platform and help deliver smarter, real-time ad targeting around trending content. While X may face serious regulatory friction as it pushes into payments and investing, the potential upside is significant. If it works, X could carve out a unique lane that blends trading, tipping, and transacting in one appterritory even Tesla (NASDAQ:TSLA) hasn't touched. This article first appeared on GuruFocus.
Yahoo
9 hours ago
- Business
- Yahoo
Startup claims to settle cross-border payments in 5 seconds using stablecoins
Startup claims to settle cross-border payments in 5 seconds using stablecoins originally appeared on TheStreet. Global payments remain slow, expensive, and fragmented—especially for businesses operating across borders. Mesta, a U.S.-based startup, is aiming to address that challenge by combining stablecoins, fiat rails, and an API-first approach to simplify cross-border transactions for fintech platforms and enterprise clients. 'Mesta is a global fiat plus stablecoin payment network,' said Sandeep Pyapali, head of payments during an interview with TheStreet Roundtable. 'We're focused on making international money movement faster and more cost-effective.' Mesta enables platforms to send payments using stablecoins like USDC or USDT, then convert to local fiat currencies for delivery. The result, according to Pyapali, is significantly lower fees and significantly faster settlement times, with some transactions clearing in under five seconds. For many businesses, blockchain remains a complex and opaque space. Mesta's approach attempts to abstract much of the underlying technology, offering a single API for cross-border payments without requiring clients to manage crypto infrastructure directly. 'Most businesses don't want to learn how stablecoins work—they just want to make payments,' Pyapali said. This model resembles what other platforms like Circle have tried to achieve—reducing friction around blockchain adoption by handling the technical and regulatory layers behind the scenes. Mesta currently supports payments in more than 50 currencies and has processed $5 billion in volume as of Q4 2024, across over 200 platform integrations. 'Our customers are primarily fintech platforms,' Pyapali said. 'They're using stablecoins for cross-border payments and tapping into local rails for delivery.' Stablecoins currently have a market capitalization of over $250 billion, but experts believe this could go to trillions by 2030. In the U.S., the GENIUS Act, a stablecoin regulation bill, passed the Senate with support from both parties to cheers from crypto holders. Circle, who issues the stablecoin USDC, recently IPO'd on June 5th at $31 per share. At press time, it was up over 500%, at $199.59, showing clear appetite for stablecoins from traditional markets. Startup claims to settle cross-border payments in 5 seconds using stablecoins first appeared on TheStreet on Jun 19, 2025 This story was originally reported by TheStreet on Jun 19, 2025, where it first appeared.
Yahoo
12 hours ago
- Business
- Yahoo
Will commercial VRPs transform B2B payments in the UK?
Adflex has been at the forefront of the B2B fintech revolution since its launch in 2001. It is known for its commitment to innovation and helping companies unlock the potential of digital payments. It covers a range of technologies including travel data, B2B procurement, B2C payments, supplier on-boarding, BACS, SEPA, ACH and hybrid card/BACS payment systems. Pat Bermingham has been CEO at Adflex since the firm launched and is ideally placed to discuss the potential for B2B payments to catch up with their B2C counterparts. He argus that corporate buyers will soon expect the same simplicity as they get when buying items in their personal lives. Take more nuanced services like Variable Recurring Payments (VRP). VRPs are simply an evolution of the current direct debit scheme. They allow a business to make a series of payments ahead of time to better forecast spend and facilitate more informed decisions. One of the most common uses for VRPs in the UK is 'sweeping'. It was back in Autumn last year that the Competition and Markets Authority (CMA) announced that all nine major banks under its remit had now implemented key open banking services, which included Variable Recurring Payments (VRPs) for 'sweeping'. Sweeping lets banking customers set up automated transfers between their bank accounts, based on pre-defined instructions. This might be transferring money from a current account to a savings account to access better interest rates or moving money to avoid going into an unarranged overdraft. Implementing sweeping was for sure an important milestone in the roll out of VRPs, but its impact hasn't been transformative. For VRPs to reach the levels of adoption that many analyst houses are predicting, more use cases need to be rolled out beyond just sweeping, and without stating the obvious, the roll outs need to go well. The good news is that this year, the Financial Conduct Authority (FCA) is overseeing new implementations of Commercial VRPs (cVRPs). A 'standard' VRP allows users to move money between their own accounts. A cVRP uses the same functionality as a VRP, but for consumer to businesses (C2B), or business to business (B2B) payments. You might be thinking, 'but isn't that very similar to Direct Debit?'. In some ways, yes: both allow users to set up automated, regular payments. However, cVRPs also enable automatic adjustments to a payment, without needing to take any manual action, so long as they're within the initial terms agreed. Take a monthly subscription as an example, such as an Audible subscription. With cVRPs, I could set up a term for my Audible subscription that stops payment being taken if my bank account is overdrawn. Or, Audible could in theory offer varying subscription rates based on how many books I actually listen to during a month, scaling up or down automatically based on my usage. Direct Debit cannot do these things. As more and more businesses switch to monthly subscription models for payments, VRPs and cVRPs are far better suited for modern payment behaviours. As I briefly mentioned earlier, the FCA recently assumed ownership of regulatory oversight for open banking in the UK, and so will be responsible for the upcoming cVRP rollouts. 'Phase 1' of this roll-out will include 'lower-risk' cVRP use cases, such as local and central government payments, utility payments and charity donations. You can expect to see these rollouts begin from Q3 this year. On 9 April 2025, Open Banking Limited (OBL) published the Commercial Model for this 'Phase 1' roll out and is currently asking for feedback on the proposed model from industry stakeholders. The deadline for sharing feedback is 16 May 2025. A cVRP multilateral agreement (MLA) is also in the final stages of development, designed to enable easier market access for participants and to provide clarity on the required functionality, pricing, dispute resolution and liability of cVRPs. This rollout is undoubtedly a significant and critical milestone for VRPs. If it goes well, then I expect we'll start to see cVRPs in loads of different C2B payment scenarios. There is also huge potential for cVRPs in the trillion-dollar B2B payment space, where we could witness the most concrete success story in the open banking era so far. In a word: yes. Many businesses today are still spending far too much time managing payments. I've spoken to multiple finance departments that spend up to one working week every month managing payments! That's staggering to me when it simply doesn't have to be like this. cVRPs are one digital solution that could open the door to huge time savings. In the B2B space, cVRPs enable a buyer to set up several payments in one go, reducing administrative overhead. cVRPs enable you to flex the timing and amount of a recurring payment based on the level of service delivered, giving greater control and power to the buyer, while facilitating real-time settlement. This can result in healthier cashflow and better liquidity for businesses. cVRPs also offer better visibility of incoming and outgoing payments compared to manual solutions, enabling businesses to operate with confidence, reinvesting and growing their operations in a sustainable and measured way. A big attraction for businesses will undoubtedly be that, as an A2A payment process, cVRPs also bypass card schemes, potentially avoiding interchange fees. This would benefit businesses operating at scale, or SMEs operating with tight margins. cVRPs also boost payment security, employing Strong Customer Authentication (SCA) – a requirement of the Second Payment Services Directive (PSD2) – at the start of the payment process, verifying identity before any funds are transferred, enhancing convenience and reducing the risk of fraud. Both yes and no. By lowering administrative demands on recurring invoices, such as payments for regular stock, IT subscriptions or licenses, or payments to the supply chain and subcontractors, cVRPs will be extremely beneficial to many firms. But despite the benefits I just outline, a key difficulty cVRPs face is that other payment methods, like commercial cards, are already woven into business payment systems, as well as in the wallets of commercial cardholders, who stand to gain from attractive reward programs. B2B transactions can be complex, requiring multiple layers of authorisation that VRPs aren't equipped to handle. Commercial cards enable tracking tools and extended payment terms that can be preferable to many business buyers. So, I believe cVRPs will likely complement, not replace, commercial (or indeed, virtual) cards. They are well-suited to recurring invoices, for regular, predictable supplier payments. But more needs to be done before we can reach this point: better technical integration, more regulatory oversight, closer collaboration between banks, TPPs (third-party providers), and learning from the lower-risk rollouts taking place this year. Cards will remain dominant for big-ticket transactions, but if managed well, cVRPs could help lighten the load, managing regular, flexible payments and encouraging prompt payment, preferred supplier status and repeat business. "Will commercial VRPs transform B2B payments in the UK?" was originally created and published by Electronic Payments International, a GlobalData owned brand. The information on this site has been included in good faith for general informational purposes only. It is not intended to amount to advice on which you should rely, and we give no representation, warranty or guarantee, whether express or implied as to its accuracy or completeness. You must obtain professional or specialist advice before taking, or refraining from, any action on the basis of the content on our site. Sign in to access your portfolio
