The company, which operates as a compliance-first, local-first model with regulated coverage across Europe, Latin America, Nigeria, and the United States, provides fintech platforms (including payroll, cross-border payments, digital banking, and spend management solutions) with the ability to issue globally accepted payment cards, funded directly from stablecoins, bridging the gap between on-chain settlement and real-world payments.

With this latest round, Kulipa’s total funding reaches USD 9.2 million. The company wants to use the capital to create solutions that will make stablecoin spending seamless and widely accepted, just like traditional card payments, helping the fintech industry to operate as a fully integrated model, where industry players will act like on-chain-enabled financial institutions.

Kulipa’s successful fundraising also comes amid stablecoins becoming the new normal in the virtual payment space, settling more than USD 300 billion daily. However, the cryptocurrency still has a drawback: a lack of efficient infrastructure connecting on-chain settlement systems with regulated card networks.

“Existing solutions are often fragmented, capital-intensive, and dependent on prefunded structures and region-specific licenses. As regulatory clarity improves worldwide, fintech companies increasingly require compliant, scalable issuing infrastructure to convert stablecoin balances into usable financial products,” reported Africa Business.

To resolve this problem, Kulipa’s stablecoin-native issuing platform has been tailored to address challenges such as capital efficiency, regulatory compliance and global scalability. Fintech partners using the company’s solution are now launching payment programmes funded directly from stablecoin balances, supporting rapid prefunded deployments and deep wallet-native integrations.

“Stablecoins have proven their value as a settlement layer, but using them in everyday financial products is still early. Card issuance is the bridge between on-chain balances and real-world payments. We built Kulipa to give regulated fintech platforms the compliant, capital-efficient infrastructure they need to operate at a global scale,” said Axel Cateland, Founder and CEO of Kulipa, while interacting with Africa Business.

By verifying balances and settling transactions on-chain, Kulipa has reduced the fintech industry’s reliance on collateral-heavy prefunding models and enabled more sustainable scaling. Stablecoin cards issued via Kulipa can be used everywhere, including retail payments and ATM withdrawals. Kulipa also assumes the role of performing fraud liability, removing a massive operational burden for fintech partners.

The post Stablecoin card issuer Kulipa raises fresh funding appeared first on International Finance.

Through the sandbox, the Egyptian government wants to promote the widespread adoption of fintech, expanding digital services in non-banking financial activities. Lumin Soft specialises in digital identity solutions, electronic verification and digital contracting technologies. It recently submitted a project that would verify the identity of non-Egyptians using electronic passports (e-passports) through Near Field Communication (NFC) technology, enabling the creation of an integrated digital pathway for identity verification via smartphone devices.

Islam Azzam, Chairperson of the FRA, told the Daily News Egypt that such digital mechanisms represent an important step toward facilitating the entry of foreign investors into the North African country’s market, enabling them to access non-banking financial services.

“Simplifying procedures for identifying and verifying investors’ identities through secure digital channels would help strengthen foreign investment flows into Egypt,” the senior official stated further.

Lumin Soft’s project relies on reading and verifying e-passport data in accordance with the International Civil Aviation Organisation Public Key Directory (PKD) standards, ensuring both data security and reliability throughout the verification process.

Azzam further added that adopting advanced technological solutions in financial services aligns with the government’s broader strategy to position Egypt as a regional fintech hub.

“Supporting digital innovation and strengthening the technological infrastructure of the financial sector will enhance the competitiveness of the Egyptian market and attract more fintech companies,” he noted.

The regulatory sandbox launched by the FRA serves as a key regulatory tool, not only in terms of supporting innovation in the financial sector and providing a supervised testing environment that allows companies to trial innovative business models and technological solutions before bringing them to the market.

“Through its participation in the sandbox, Lumin Soft will be able to conduct live testing of its business model within the regulatory framework. This includes creating digital identities using e-passports and integrating with the Azimut Investments Egypt platform, enabling investors to access financial products within a regulated supervisory environment,” Daily News Egypt reported.

Ahmed Khalifa, Executive Director of the FRA’s regulatory sandbox, said the project will help non-Egyptians access investment services across various asset classes in the Egyptian market while enhancing the efficiency and competitiveness of the non-banking financial sector (NBFC).

The post Lumin Soft becomes third company to join Egypt’s fintech regulatory sandbox appeared first on International Finance.

Revolut, which was recently cleared by the United Kingdom’s regulators to launch its bank in the European country, said its revenue was 4.5 billion pounds, up from 3.1 billion the previous year, driven by income from fees charged to its 68.3 million customers.

The company more than doubled its loans to customers, with its lending portfolio (mostly consumer loans) growing ‌120% to 2.2 billion pounds. Since its formation in 2015, Revolut has emerged as the most successful of the handful of European fintech companies founded in the ⁠2010s, with no physical branches. In November 2025, the venture hit a USD 75 billion valuation in a private secondary share sale.

The approval from the Bank of England’s Prudential Regulation Authority now allows the company to end its “mobilisation” phase, which lasted for longer than the usual 12-month limit.

“This allows Revolut to offer protected deposit accounts and paves the way for a wider range of services in future, including lending and other products,” the fintech venture remarked.

Predicting that the process of moving customers to the new bank will take “a few months in total,” Nik Storonsky, Revolut’s co-founder and CEO, remarked, “Launching our UK bank has been a long-term strategic priority for Revolut, and marks a significant moment in our journey. The UK is our home market and ‌central to our growth.”

“The full licence will open the door to balance sheet-driven products and sharpen pressure on both traditional banks and the cohort of challenger banks,” said Elliot Reader, Director in Houlihan Lokey’s FinTech Group, while interacting with Reuters.

The company ⁠is also seeking a banking licence in France, although it already offers banking services in the European Union by “passporting” a ⁠licence from Lithuania, and has applied for a bank charter in the United States.

The post With record USD 2.3 billion in 2025, Revolut witnesses 57% jump in pretax profit appeared first on International Finance.

Across global banking systems, artificial intelligence is moving from back-office optimisation to the heart of credit decision-making. The shift is subtle. There are no public announcements declaring that machines now approve mortgages. Yet increasingly, algorithms analyze income, spending patterns, behavioural signals, and even alternative data before a human ever sees an application.

So, the question is unavoidable: Are machines deciding who gets loans? And if so, what happens to human judgement?

The Quiet Expansion Of AI In Lending

Artificial intelligence is already deeply embedded in financial services.

“AI is transforming banking quite significantly, and the pace of adoption is fast,” Wahyu Jatmiko, Assistant Professor in Banking and Finance at the University of Southampton Business School, told International Finance.

He points to data from the Bank of England and Financial Conduct Authority showing that around 75% of UK financial institutions were using AI by 2024, up from 58% just two years earlier.

However, he explains, the heavy use remains concentrated in internal optimisation, cybersecurity and fraud detection. In underwriting specifically, adoption is more measured.

“Roughly around 15% of firms use AI directly in credit underwriting,” he estimates.

That figure may sound modest. But the deeper shift is structural.

“Even where it is not fully taking over, AI is increasingly embedded in the process,” Jatmiko says.

Instead of relying entirely on traditional credit bureau scores, systems now analyse real-time transaction data, behavioural patterns, and alternative datasets.

The result is not necessarily that machines approve all loans. Underwriting is becoming faster, more data-driven, and far more granular.

James Ekpa, an AI researcher at the Blockchain Technology Association for Black & Minority Ethnic Engineers (AFBE-UK), did not mince words.

“Yes, machines are increasingly deciding who gets loans today,” he told International Finance.

He sees a transformation from slow, manual processes to rapid, automated systems powered by machine learning algorithms.

Speed, consistency and scalability are among AI’s biggest advantages. Decisions can be made quickly. Models apply the given criteria uniformly. And, algorithms can analyse thousands of variables at a scale humans simply cannot match.

Efficiency, in other words, is no longer the differentiator. It is the baseline expectation.

Enhancement Or Replacement?

But, does faster mean better? And more importantly, does faster mean human judgement is fading?

“At the moment, I clearly see AI as enhancing human judgement rather than replacing it,” Jatmiko says.

He cites UK data suggesting that while about 55% of AI applications involve some automated decision-making, only around 2% are fully autonomous.

Creditworthiness, he argues, is not merely about predicting default probabilities. It involves context, borrower circumstances, regulatory constraints, and sometimes ethical considerations.

AI excels at analysing large datasets, document reading, income verification, and affordability calculations. In that sense, Jatmiko says, it acts like a powerful analyst. But final approvals, particularly for complex or high-value loans, still rest with humans.

Ekpa agrees that the human role is evolving rather than disappearing. Loan officers today increasingly review edge cases and borderline applications. They handle complex deals. They explain decisions to customers. They monitor model outputs and escalate anomalies.

The job is changing. It is becoming supervisory. That may be the real transformation.

When Context Meets Code

The limits of automation become clearer when qualitative factors enter the picture.

Jatmiko describes a hypothetical but realistic scenario: a small business reporting temporary losses due to a supply chain shock while holding strong long-term contracts. A human underwriter may interpret the broader narrative and take a forward-looking view. An algorithm trained primarily on historical default data might simply detect recent losses and flag high risk.

“There is research showing a mismatch between what AI models consider important and what human loan officers see as meaningful indicators of creditworthiness,” he explains.

Humans can contextualise. They can sometimes account for structural disadvantages when justified by circumstances. AI, by design, optimises patterns found in historical data. That difference is subtle. But in lending, subtle differences affect livelihoods.

The Question Of Bias

Advocates of AI argue that machines eliminate prejudice. Algorithms do not discriminate intentionally. They do not favour friends. They apply rules consistently. And that consistency is powerful.

But, consistency applied to flawed historical data can create new problems.

“AI can reduce certain types of human bias, but it can also embed and even amplify systemic bias,” Jatmiko explains.

If past lending patterns reflected unequal treatment of certain demographic groups, models trained on that data may internalise those patterns as objective signals of risk.

Ekpa echoes this concern. One of the primary risks, he notes, is bias amplification. If historical data contains discrimination, models may encode and intensify it.

Transparency is another issue. Complex models can be difficult to explain. Borrowers denied credit may receive little more than a generic explanation.

“Opacity raises regulatory and consumer trust concerns,” Ekpa warns.

Then there is model drift, when changing economic conditions gradually degrade model performance. Without continuous monitoring, systems may misprice risk during volatile periods.

In short, bias does not disappear. It changes form.

Accountability In An Algorithmic Age

If an AI-driven system denies a borrower unfairly, who is responsible? The answer is not always clear. Multiple actors are involved – AI manufacturers, developers, third-party providers, and lenders themselves.

However, both experts converge on one principle: accountability ultimately rests with the financial institution.

Ekpa says AI is a tool, not a legal entity. Financial institutions remain responsible for the models they deploy, the data they use, and the governance frameworks they maintain.

Jatmiko does not overcomplicate it. If a loan decision turns out to be unfair, the algorithm cannot be the one blamed. The bank chose to use it, so the bank carries the responsibility. That means senior leaders cannot hide behind technical language. They have to stand behind the outcomes.

He stresses that human oversight is not optional, especially for complicated or sensitive cases. Models need regular checks. They need to be tested for bias. They need proper audit trails. Otherwise, problems build quietly.

He also worries about something bigger. If many banks start depending on the same AI providers, risk can pile up across the system. One flaw could affect more than just one institution. Efficiency is important. But, it cannot come before accountability.

The Islamic Finance Lens

From an Islamic finance point of view, this is not just a technical debate. It goes deeper than that. Islamic banking is guided by Maqasid al-Shariah, ideas around justice, fairness, and social welfare. Lending is not only about numbers on a balance sheet. It carries a social responsibility.

Yes, AI can make processes smoother. Faster approvals. Cleaner risk models. That part is clear. But Jatmiko flags something more subtle. If the data used to train these systems reflects a past where small businesses were routinely sidelined, the algorithm may quietly repeat that history.

And if that happens, the technology could end up working against the very goals Islamic finance is supposed to protect. Not intentionally, but just by following patterns.

Aligning AI with ethical principles requires intentional intervention in model design and governance. It may require bringing social scientists into AI development processes. It may demand stronger oversight, particularly when tools are sourced from third-party providers.

Technology alone does not guarantee fairness. Design choices matter.

Possibility Of A Hybrid Future

So, where is banking headed? Fully automated lending systems may emerge in low-risk, low-value segments. Routine cases can be processed at speed and scale. But both experts see the broader future as hybrid.

Ekpa believes competitive advantage will come from institutions that combine AI’s analytical power with human judgement, rather than eliminating one in favour of the other.

Jatmiko similarly expects automation to expand, but insists that human supervision will remain essential, especially for complex or high-impact decisions.

Human-in-the-loop processes are already becoming common. Algorithms analyse. Humans validate. Decisions are checked before final approval. Perhaps, the future banker will not be replaced, but repositioned.

The Big Question

For borrowers, the shift may be invisible. Applications are approved faster. Rejections arrive more quickly, too. What changes quietly, beneath the surface, is how those decisions are made.

Is human judgement fading? Or simply moving further upstream, designing and supervising the systems that now perform the analysis?

The rise of the AI loan officer is not dramatic. No headlines are announcing the end of human bankers. Instead, there is gradual integration, more data, faster models, and shorter decision times.

Machines are increasingly involved. That much is clear. But whether they ultimately decide, or merely assist, depends less on technological capability and more on governance choices.

Banks can treat AI as an efficiency engine. Or, they can treat it as a tool that augments, rather than overrides, human responsibility. The distinction may determine not only how loans are approved, but how trust in the financial system evolves in the years ahead. And trust, unlike data, cannot be automated.

The post Are humans making way for AI loan officers? appeared first on International Finance.

In an online survey of 225 mid-market finance and accounting leaders, conducted in September 2025, only 4% of respondents admitted to fully automating AP from invoice to payment with no manual touchpoints. The respondents reported annual revenue between USD 20 million and USD 499 million.

The survey, titled “The State of AP Maturity 2026: Closing the Gaps Between Partial and Unified Automation,” included respondents across healthcare, retail and hospitality sectors. About 48% of them reported witnessing “little to no cost savings” from their AP automation tools.

Ottimate attributed the issue to the prevalence of “partial automation,” where humans and machines collaborate on tasks. While 89% of respondents use partial automation in the AP function, 7% reported completely depending upon human interventions to complete tasks.

“Partial automation may seem like a step in the right direction. But it actually sets the stage for some of the key challenges finance teams face every day,” Ottimate noted.

While half of the survey respondents filed more than 5,000 invoices monthly, 38% currently take five or more days to process a single invoice.

“While that timeline may not seem particularly problematic, it quickly becomes unmanageable when multiplied across thousands of invoices,” Ottimate’s report observed, noting that this trend occurs amid the growing prevalence of AI-powered frauds. The survey also found four in 10 respondents experienced either invoice fraud or overpayment in 2025.

The study found that when fighting fraud for midsize firms, manual invoice reviews before payment remain the preferred financial control. Some 52% of the respondents cited this method as their most favourite financial control tool, and another 50% said they require two or more approvers before releasing a payment.

The post AP automation: Survey depicts poor picture for mid-market firms appeared first on International Finance.

However, both have one thing in common, which is a complex and time-consuming process, requiring companies to post the A-Z of their business operations, including management’s perspective on the previous year’s performance and financial condition, along with the status of pending lawsuits.

Despite legacy platforms like Workiva (aa major name in terms of providing cloud-based software-as-a-service to American companies) and Donnelley Financial Solutions doing their best in streamlining financial reporting, longtime accountants Mary Antony and Kelsey Gootnick, along with Jared Tibshraeny, a software veteran with 15-plus years of experience building and scaling web applications, felt the need of disrupting the forms 10-K and 10-Q submission-related practices in a way, where technology will simplify the practices of patching together spreadsheets, moving into bunches of word documents and back and forth emails between people within a financial set-up.

The result was the formation of InScope in 2023, an AI-powered financial reporting platform that is now helping companies and accounting firms automate a significant portion of the financial statement preparation process. InScope was launched in 2026 on a positive note, by raising USD 14.5 million in Series A funding led by Norwest, with participation from Storm Ventures and existing backers Better Tomorrow Ventures and Lightspeed Venture Partners.

Tech Making Tedious Tasks Easy

Instead of fully automating the generation of income statements and balance sheets, the venture has automated a vast amount of the manual busy work, from verifying math to formatting. According to Mary Antony, InScope’s CEO, the platform is making accountants’ lives easier through simple actions, such as uniformly and correctly placing dollar signs and commas on the 10-K and 10-Q forms, ultimately saving users up to 20% of their time.

Customised for GAAP (Generally Accepted Accounting Principles) financial reporting, InScope has been proven helpful for the American segment, representing small to medium enterprises, to large, multinational corporations, by eliminating 80% of manual tasks in financial reporting.

Functions like auto-roll forward, auto-formatting and linking plus syncing are allowing the start-up’s customers to get out of mundane tasks. Manual processes sometimes fail to catch errors and discrepancies. However, Inscope’s “AI Assistants” smooth out things here as well, by ensuring accuracy and internal consistency of financial statements.

For accounting firms, the start-up automates the financial statements preparation and review process by making sure its autopilot goes above the traditional functions of tagging and filing financial details, ending up automating the tiresome work of preparing accurate, compliant financials.

First-draft financials get generated in hours, not days, while AI-Assisted footing, cross-footing, and internal consistency checks slash data review time by up to 70 %. Not only can accounting firms live sync the solution with their Excel workbook, to keep numbers final and eliminate version chaos, features like consistent rounding, clean formatting and tracked changes ensure fewer audit notes and most importantly, satisfied clients, while freeing up senior industry talents for higher-value strategic and advisory works.

InScope’s smart technology and productivity-oriented solutions have helped the company grow its customer base by five times since 2025, also attracting significant American accounting firms such as CohnReznick.

As mentioned earlier, InScope is helping companies and audit firms to draft their forms 10-K and 10-Q in a better and faster manner, by instantly carrying forward prior-year financials, footnotes, and disclosures, without worrying too much about copy-paste or formatting.

Following this, the start-up’s AI takes over the preparation function by suggesting the required disclosures to its users based on their business documents, company details, and industry peers. Then all the details get inserted in SEC-ready, audit-compliant tables with a single paste.

Before the forms go for SEC filing, AI-powered “Review Assistant” scans the documents for footing, cross-footing, and internal consistency errors across the client’s entire document. The process also flags language that may be inconsistent with prior filings or peer disclosures. Also, version history, milestones, and blacklines make every change traceable and review-ready.

The McDirmit Davis Case Study

Florida-based accountant McDirmit Davis assurance practice handles complex financial reporting that legacy tools simply can’t handle reliably. The business’ workflow of linking heavy Excel files into Word Documents used to create a fragile ecosystem where broken links and file corruption, constant file crashes were constant risks. As it turned out, InScope, the start-up, moved quickly, rolling out the platform to the entire staff, from partners to associates, establishing the platform as the accountancy firm’s new standard for deliverables.

Simplifying McDirmit Davis’ experience with Excel, InScope has created an ecosystem where the accountancy firm’s team can make entry-level changes that flow through to the financials instantly, without the risk of the document crashing or links breaking.

Inscope’s AI is also acting as an intelligent second set of eyes, by proactively scanning financial data (for example, identifying long-term debt disclosure) and suggesting missing accounting policies, catching omissions that human reviewers might overlook.

When McDirmit Davis’ team of human accountants identifies a need, whether it’s better formatting controls or granular permissions, Inscope iterates immediately. The platform also automates the ticking and tying process, eliminating the manual “tabular” checking required by other tools and in the process, while freeing up senior staff for high-value review.

The team-up between McDirmit Davis and InScope has already produced wonders. Apart from eliminating version crashes by replacing the “crash and malfunction” cycle of embedded tables in Microsoft Word with a stable, cloud-based platform, the start-up has also installed a mechanism of proactive quality control for the accountancy firm, with AI agents identifying missing disclosures and policy gaps before they reach the final review stage.

Seamless review and edit cycles allow human professionals to address comments and make rapid adjustments without breaking the underlying data structure. Finally, through 100% staff adoption, InScope has successfully onboarded the entire McDirmit Davis team to a single platform.

The post Start-up of the Week: Using tech’s helping hand, InScope makes SEC filings a seamless affair appeared first on International Finance.

Not only Amodei and Brockman, but Duco van Lanschot and David Schreiber also came into the limelight by creating the business identity verification startup Duna. The start-up recently raised a 30-million-euro Series A to become the best-funded European member of the so-called “Stripe Mafia.”

Based in Germany and the Netherlands, Duna has a rich portfolio of customers, including American financial services company Plaid. Duna helps fintech companies onboard business customers more efficiently, reducing the typical churn associated with corporate ID checks and other fraud prevention measures.

Creating Digital Passports For Companies

According to Duco van Lanschot, Stripe is not a typical customer of Duna, with the fintech giant’s executives understanding the opportunity that the start-up was about to seize in terms of making the process of onboarding business customers simpler and more efficient. What followed was big shots like former Stripe executives David Singleton, Claire Hughes Johnson, and Michael Cocoman getting involved in the funding round as angel investors. Even Stripe rival Adyen participated in the round.

Now, what exactly is the start-up trying to achieve? Apart from going after the long tail of enterprise clients that don’t have huge resources to dedicate to business onboarding, Duna sees its existential future in a world where there will be a network that allows companies to reuse their verified identity information across multiple platforms through a digital passport mechanism.

This goal resonated with Alex Nichols, the general partner who led CapitalG’s investment into the Series A. For Nichols, what sets Duna apart is its decision to generate its own data, rather than trying to aggregate existing data sources that are often lacking.

While Duna has reportedly found a strong business case in helping customers onboard corporate users faster and cheaper, existing investors are further doubling down. Index Ventures, which led Duna’s 10.7-million-euro seed round in May 2025, participated in the Series A, as did Puzzle Ventures and Frank Slootman, chairman of Snowflake.

However, to fulfil the immediate goal of reaching scale, Duna is taking shortcuts by identifying small clusters of companies that already overlap with each other. The start-up calls them “patches of networks.” These include manufacturing companies with shared customers, investment firms with overlapping LPs, or companies in the same small country. In Duco van Lanschot’s opinion, in these tight-knit groups, the ability to reuse verification becomes valuable immediately, even before Duna achieves full network effects.

Instead of replacing these jobs, Duna, through its AI automation, wants to help human professionals save costs and generate revenue even before the network effects kick in. If Duna eventually provides the rails for an identity network, Duco van Lanschot sees a bigger opportunity opening for the start-up, where the venture will enable one-click business onboarding.

The Products

Duna’s “Onboard,” built with the standards of regulated enterprises top of mind, provides compliant onboarding journeys optimised for conversion. The product helps its users access 20-plus ready-made KYB (Know Your Business) modules (including business details, legal representatives, ownership and UBO, AML screening, bank account, and address proof), apart from fine-tuning every data field to fit their enterprise needs.

Through the solution, Duna’s team of engineers and designers takes over their clients’ headache of converting potential leads into sales by dynamically shaping onboarding based on risk scoring, assessing data points in real time, and adapting journeys automatically. Businesses also get to avoid losing customers by asking for basic information at account creation and collecting additional KYC data based on product usage.

Companies can facilitate private interactions with legal representatives and Ultimate Beneficial Owners (UBOs) to collect essential information such as identity verification, source of funds, contract signatures, and more. Most importantly, instead of using separate onboarding platforms for different products, companies can save money by consolidating all solutions and their varying compliance policies under one digital umbrella.

Next is “Decide,” Duna’s automated case management mechanism, which increases compliance quality and reduces costs by cutting out lengthy reviews, manual checks, and endless email back-and-forth. The solution standardises these tedious functions by automatically adapting workflows based on risk signals, customer type, and compliance policies, leveraging AI and various other KYC technologies that verify and extract customer documents.

If a financial company has its pre-set compliance criteria, all it needs to do is feed the details into the automated case management system, after which it will take over the task of approving customer applications as per the established rules.

The solution also scores high on the AML (Anti-Money Laundering) front by fully automating hits on PEP (Politically Exposed Person), sanctions, and adverse media, with outsourced OSINT (Open-Source Intelligence) investigations. Duna’s automated case management mechanism has already proven its worth through its ongoing stint with some of the trusted names in the global financial industry, including Moody’s, Fourthline, LexisNexis, SurePay, Creditsafe, and IDnow.

Innovation Simplifying Things

Another excellent piece of Duna’s innovation is “Lifecycle,” which manages compliance throughout the customer lifecycle. Regulation meets retention with perpetual KYC, daily screening, re-KYC, policy versioning, and management of legal agreements.

Lifecycle is special because it automatically monitors Politically Exposed Persons (PEPs), sanctions, and adverse media related to business customers, individuals, and affiliated organisations. In addition, it tracks changes in registry data, such as legal names, addresses, and representatives. Lifecycle initiates re-Know Your Customer (KYC) processes based on real-time insights from registries, media, and open-source data. It also establishes re-verification frequencies tailored to the risk levels and timeframes of client companies.

The solution addresses evolving compliance requirements through a single interface that allows for the rollout of updated policies across various products, embedded finance partners, and jurisdictions. It implements ongoing changes based on regulations, product developments, and risk appetite, while also applying different policies according to regulatory jurisdictions. Additionally, it streamlines policy requirements across the financial partners of the client’s business.

The post Start-up of the Week: Duna targets one-click business onboarding appeared first on International Finance.

Launched in 2022, the company has carved out an AI-driven tax intelligence that’s as compassionate as it is cutting-edge, helping human accountants to navigate the complex and quickly changing tax codes. The company’s emergence also coincided with the rise of generative AI and transformational forces like OpenAI (creator of ChatGPT). Using the Sam Altman-led tech venture’s GPT technology, Muse disrupted the financial industry by connecting its digital platform to AI through software bridges known as application programming interfaces (APIs).

Established by public accountants Colin Horsford and Busayo Ogunsanya, Muse has built its own software on top of the OpenAI platform. Data and precise analytics have become the venture’s key tools to build a better operational future for financial institutions.

Knowing The Company In Detail

The company follows a business-to-business model, where it stitches up partnerships with financial institutions. Back in 2022, Muse Tax was funded with a combination of investments by its founders, as well as about USD 350,000 in pre-seed capital from early-stage investors, including “Techstars,” the “AI Operators Fund,” and “Everywhere Ventures,” formerly known as “The Fund.” Then, in 2023, it raised a USD 2 million seed round.

Horsford, who is himself a financial industry veteran (as he worked with American International Group, Goldman Sachs Group, and other financial-services companies), during an interaction with The Wall Street Journal in 2023, explained the company’s operations in the following words: “Users feed their tax returns and transaction data into the Muse Tax system, which can keep track of all the latest updates to the tax codes. The system recommends ways in which the user can keep tax bills to a minimum.”

“You have to stay abreast. During the COVID pandemic, there were so many tax changes that preparers and accountants missed some. That is really what our model is trained to do—to be more up-to-date and process information a lot faster than the average human preparer or accountant, even if they are very experienced,” he stated.

Muse Tax usually can make tax recommendations in 20 to 30 seconds—sometimes as long as 45 seconds—as opposed to their human counterparts, who generally take five to seven hours for comparable advice and cost more. Why does the company use GPT? Because the latter can synthesise and summarise information, including the tax-related ones, in the blink of an eye. However, it doesn’t mean that AI does everything at the start-up, as Muse has put together procedures to oversee the AI’s responses.

Here Are The Key Products

Among Muse Tax’s key products, we have CheckBoost, which boosts customer paychecks by up to USD 200, apart from creating opportunities for them to pay down debt, save, or invest. The start-up’s advanced algorithms suggest alterations that maximise financial well-being, which potentially leads to increased take-home pay. CheckBoost also optimises tax withholdings for a more stable financial flow and customers with quicker access to their refunds. The solution also ensures the information entered in the W-4 (Employee’s Withholding Certificate, an IRS tax form used by employees to inform their employer of the correct amount of federal income tax to withhold from their paycheck) is accurate and aligned with the latest tax regulations.

CheckBoost also automatically transfers funds to high-yield savings accounts, helping its customer companies pay off debt, make investments, and more. Employees can enjoy increased take-home pay while experiencing better financial wellness.

“CheckBoost stays current with the latest tax laws, minimising the mental burden of updating a W-4 and reducing tax-related confusion for workers. By using CheckBoost, workers gain more control over their finances, positively affecting their mental well-being by offering clarity and simplifying financial decision-making,” the start-up commented.

“CheckBoost boosts employee paychecks by up to USD 200. We optimise their tax withholdings; they get more take-home pay. Employees can use their increased pay to buy groceries, save, or take that vacation that they’ve always wanted to take,” it added.

Another innovative tool is MuseScore, which quantifies its users’ financial profile, apart from giving them a score like a credit score. It helps individuals understand their current financial situation, find saving opportunities, and provides constant monitoring of their financial health to help them make the most of their disposable income.

Muse Score quantifies its users’ tax profile, offering clarity on their overall financial health and guiding them towards financial improvement. The start-up explained its product in the following words: “By revealing your tax situation, Muse Score identifies potential savings and strategies to enhance your tax efficiency. It’s as insightful as a credit score. Muse Score enables near real-time insights into possible deductions, credits, and your projected tax liability or refund throughout the year.”

How does MuseScore work? The solution assesses its users’ disposable income and tax burden to generate a centralised score. The score gets standardised on a 350 to 850 scale, similar to the solution’s users’ credit score, while taking into consideration factors like the cost of living, total taxable income, and dependent deduction. The score also evolves as an individual’s financial situation changes. Things such as a bump in disposable income or the birth of a child could change the tax optimisations. MuseScore considers these factors while keeping its customers informed about their tax optimisation.

Also, “Muse Compass” pulls data from a business’ key sources, including bank accounts, payroll, QuickBooks, spreadsheets, and more, before leveraging the AI to recommend the best solutions based on the business’s market situation. The tool also has its own predictive analysis that, through financial forecasting and analytics, warns entrepreneurs beforehand about an impending financial crisis.

The post Start-up of the Week: Muse Tax brings AI speed to tax compliance appeared first on International Finance.

Emirates Gold will deploy between 35 and 40 Gold ATM units across the country in 2026, forming the region’s largest network of its kind. Each ATM will hold over 70 designs of gold and silver bars, offering users convenient access to purchase bullion at any time.

“The smart Gold ATM also integrates digital payments, bullion dispensing, and advanced security features into one seamless platform. Users can currently purchase gold or silver using e-wallets or credit cards, and withdraw physical bullion from their digital accounts, with additional features such as online order collection, cryptocurrency conversion, and redeeming tokenized gold from secure vaults planned for future integration as this initiative continues to evolve,” reported Mubasher, MENA (Middle East and North Africa) region’s prominent financial information and trading platform.

The CEO of Emirates Gold DMCC, Abhijit Shah, said, “Our partnership with Public Gold brings together Emirates Gold’s trusted refinery expertise and operational strength with modern fintech innovation, setting a new global benchmark for secure and transparent bullion accessibility.”

On his part, Jerry Ng, Chief Marketing Officer of Public Gold DMCC, said, “This landmark moment places Malaysia and the UAE at the forefront of global gold innovation. Our fintech-powered Gold ATM breaks traditional barriers and makes physical gold ownership simpler, safer, and more accessible. We are proud to build this vision alongside Emirates Gold within the trusted DMCC ecosystem.”

As the network expands, Emirates Gold aims to make bullion access faster, smarter, and more secure for users across the UAE, in the pursuit of decisively shaping the future of accessible precious metals.

The post UAE witnesses launch of world’s first fintech-enabled ‘Gold ATM’ appeared first on International Finance.

As per the European Commission’s 2023 data, 99% of European businesses are small and medium-sized ones. Apart from providing jobs to more than 85 million citizens in the continent, SMEs are also driving innovation and entrepreneurship in the region, while promoting a sustainable and digital economy. The start-up wants to revolutionise the sector further by redefining the payment experience for merchants, eliminating things like hidden fees, outdated hardware, and poor customer service.

Hand-holding European SMEs To Growth Highway

Flatpay’s operational value is simple: European merchants deserve a payment solution that is easy to understand, affordable, and free from hidden fees. To execute this, the start-up is offering a straightforward pricing model with no setup fees for terminals, no subscription fees, and a flat rate for all card types.

Flatpay’s journey began in 2022 when three digital entrepreneurship and payment solution experts came together in Copenhagen to disrupt the market with a simple, transparent, and affordable payment solution for small and medium-sized merchants. Since then, it has expanded its presence to Finland, Germany, Italy, and France, while continuing to grow rapidly.

Apart from witnessing a quick growth on the customer front, Flatpay’s own valuation has grown at a similarly fast pace as well. Now valued at 1.5 billion euro (USD 1.75 billion), the Danish start-up reached unicorn status in only three years. CEO and co-founder Sander Janca-Jensen, while interacting with TechCrunch, said that his company recently crossed the 100-million-euro mark, when it comes to annual recurring revenue (ARR).

He added that the amount (approximately USD 116 million) is increasing by nearly 1 million euro a day (USD 1.16 million) currently. The plan for 2026, as per Jensen, is to grow another 300% and close the year with between 400-500 million euro of ARR.

The Products

Flatpay’s payment options help SMEs thrive by streamlining their order and payment processes, giving the business owners more time and freedom to focus on operational growth. Apart from keeping the customer support active on a 24/7 basis to keep the payments running smoothly, day and night. Businesses, in return, only need to pay Flatpay at simple rates, with no hidden fees.

Take the payment terminal, for example, that automates the task of creating annual payment reports by uploading transactions and Z-reports directly to the businesses’ bookkeeping systems, saving time and reducing human errors. The payment terminal provides everything an entrepreneur needs to accept major cards like Visa and Mastercard, including contactless options, in one device.

Also, the device’s intuitive interface ensures less waiting time for customers, due to lightning-fast payments. All the business owners need to do is choose the payment terminal they need for their ventures, following which Flatpay takes over, in terms of completing full on-site installation of hardware, software, and setup.

Next is Flatpay’s POS (Point of Sale) solution, which streamlines payments, product management, and sales analytics for all businesses. Designed to make accepting payments faster, easier, and stress-free, the solution tracks sales, manages inventory, and generates reports directly from the client’s business’ POS, thereby donning the role of an “all-in-one business hub.” And it also integrates seamlessly with a wide range of accounting tools.

The POS has been customised for businesses of all sizes. For small ones seeking simple payment and management tools, the solution comes with a simple, clean setup with a tablet and portable terminal. For businesses that are ready to shell out more, the premium all-in-one POS comes equipped with a 15.6″ touch screen, built-in printer, and customer-facing display.

On the online payment front, Flatpay is enabling SMEs to receive online payments quickly and securely, at a competitive price. Not only do the start-up’s technologies and encryption methods ensure protection of payments and personal information of the business owners and customers, but it is also compatible with popular payment methods like Visa, Mastercard, PayPal, Google Pay and Apple Pay.

Expanding At A Steady Pace

As Flatpay entered the league of European fintech unicorns, the start-up will use the newly raised capital to support its continued growth in Denmark, Finland, France, Germany, Italy, and the United Kingdom, as well as eyeing further expansion into one or two new markets in 2026.

Flatpay currently has 1,500 staffers, or “flatpayers,” and plans to double that by the end of 2026. Increasing headcount is another crucial goal the company has locked in on the same level as revenue, as the start-up aims to grow both by 10x by 2029.

Flatpay believes that SMB owners actively look for new solutions, even if their current systems are overpriced or insufficient. As per Janca-Jensen, “That’s where we come in the door.” The start-up’s staffers show up with pen and paper to explain its pricing, and with card terminals for instant demos.

Flatpay is betting big on this particular hands-on approach to increase its market share against legacy providers like PayPal, Stripe, and SumUp, as well as new entrants focusing on specific sectors, such as hospitality. As SMBs want operational simplicity, Flatpay is ready to provide that.

The start-up is not completely averse to AI, as it uses the technology for real-time features and is currently experimenting with voice AI agents. The venture is also planning to expand further into fintech with a banking suite that would include cards and accounts.

The post Start-up of the Week: Flatpay emerges as European fintech unicorn challenger appeared first on International Finance.