Payments firm Stripe has reportedly held initial talks with banks about using stablecoins. These discussions are happening as Stripe is rolling out a series of stablecoin-related products. “In the conversations we have with them, they’re very interested,” Stripe President and Co-Founder John Collison said. “This is not something that banks are just kind of brushing away or treating as a fad. Banks are very interested in how they should be integrated with stablecoins into their product offerings as well.” Stripe is among several companies in the FinTech space — including PayPal, FIS, and Fiserv — that are using stablecoins as a method of payment, and not just something used in crypto trading. “Regulated bank-issued stablecoins offer faster, more efficient and globally accessible payment options,” said Julia Demidova, head of digital currencies product and strategy at FIS. “With proper regulation, banks will become central players in digital assets, driving innovation while ensuring consumer protection.”
Visa’s tokenization for agentic AI payments involves three components: upgrading cards to handle agents; enabling agent transactions; and personalization to make LLM queries more relevant
Visa is experimenting with agentic artificial intelligence that would add automated execution for consumers to queries on large-language models. Executives wouldn’t put a timetable on when these products will go live, but they are being tested in internal sandboxes. Jack Forestell, San Francisco-based chief product and strategy officer, explained how the first iterations of agentic AI will work. “We formed a point of view that AI and specifically agent-driven AI has the potential to radically transform the way we discover, the way we shop and the way we buy,” he said. Forestell’s teams have thought through all of these things. This doesn’t mean the service is flawless – it’s experimental – but it’s ready to go live. Stephen Karpin, Singapore-based president of Visa’s Asia-Pacific business, says this is the latest iteration of a move by the company from organizing itself around products, toward services. “This involves a combination of our infrastructure, capabilities, and APIs to create a ‘Visa as a Service’ stack,” he said, noting this is only possible because the company has spent decades building the foundations of its payments-processing network. “We are shifting to a services architecture that includes risk management, settlement, credential directors, and now tokenization,” he said. “This is now all scaling.” Visa reckons there will be massive demand for agentic AI. Forestell noted OpenAI and the like have quickly amassed more than 1 billion active users. Traffic volume from LLM sites to retail and marketplace websites is rising fast. What’s missing is the ability to pay directly off the back of a query. LLMs don’t have access to credit-card numbers or passwords. And there’s no trust factor: consumers fear agents would misrepresent them or steal their money; banks can’t tell if an agent is legitimate; merchants aren’t confident they’ll be paid. Forestell says Intelligent Commerce has been engineered for people to buy with AI and be confident the payment is as safe and secure as it is with a credit card.
. It’s really about tokenization. This involves three components: upgrading cards to handle agents; enabling agent transactions; and personalization to make LLM queries more relevant. This AI-prep work is focused on tokenization, which payments companies have applied to other digital payments for a decade or so. This involves replacing the 16-digit number on a plastic card with a unique, cryptographically protected code, like a one-time pass that is linked to an account but if hacked doesn’t provide access to funds or instructions. This abstraction layer is being refitted for agentic AI, meaning these tokens can interact with agents. This capability is augmented by services that sync payment instructions, and signals that ensure all authorized parties in a transaction have the same access to data for processing, detecting fraud, and handling disputes.
Apollo Global is reportedly working with JPMorgan, Goldman Sachs and three other banks to trade private credit and be able to originate larger loans and continue helping individual clients who need to redeem
Apollo Global Management is reportedly working with five banks, including JPMorgan Chase & Co. and Goldman Sachs Group, to trade private credit. The collaboration will enable Apollo and its partners to syndicate investment grade debt on a larger scale, with the banks acting as broker-dealers. With the extra liquidity, Apollo will be able to originate larger loans and continue helping individual clients who need to redeem their investments more often than institutions. The collaboration came as Apollo has been working to build a marketplace for private credit deals and to increase the number of buyers on the secondary market. Banks have also planned to build trading desks for this market. The private credit market has been booming as it offers a capital “lifeline” of sorts to a variety of borrowers, especially smaller firms that have been, or still are, underserved as they seek capital from traditional markets. Private lending may also be extended to firms that are backed by private equity vehicles.
Zown, a real estate platform , is expanding into California giving buyers an upfront “down payment boost” by redirecting a portion of the buyer’s agent commission — up to 2% of the purchase price — to the buyer
Zown, a real estate platform that offers upfront financial help to homebuyers, is expanding into California with a goal to ease the burden of down payments and elevated home prices. The service has launched in the Golden State after gaining traction in Canada, where it supported more than 250 homebuyers and facilitated $300 million-plus in transactions. The platform gives buyers an upfront “down payment boost” by redirecting a portion of the buyer’s agent commission — up to 2% of the purchase price — to the buyer. Rishard Rameez, Zown’s co-founder and CEO. “Most middle-income earners are stuck paying someone else’s mortgage via monthly rent. At the same time, they earn too much to qualify for traditional assistance programs, but not enough to save for a down payment as home prices climb. That’s where Zown steps in. We’re setting a new standard for the industry by providing upfront, tangible support where buyers need it most, at the start of their journey.” Rameez added that his own frustrations as a home seller led to the creation of Zown. Zown pairs buyers with a licensed agent who uses the company’s tools — such as artificial intelligence-powered pricing insights, real-time comparable data and predictive analytics — to help navigate the market. Preapprovals are processed quickly, sometimes in under five minutes, either through a buyer’s preferred lender or Zown’s system, leaders said. A statewide network of listing agents also allows buyers to schedule home tours on demand, avoiding the bottlenecks often associated with the traditional single-agent model. Zown said it retains just 1% of the buyer’s agent commission and returns the remainder to the buyer as an upfront down payment boost — or to buy down mortgage rates and lower monthly payments. Agents are paid a salary rather than working solely on commission — a change that’s designed to encourage service over sales volume, Zown said. “Buying a home is one of life’s biggest milestones, and you deserve an agent who sees you as more than just a transaction,” said Lisa Touney, Zown’s lead real estate agent for California. “Zown’s technology was built to ensure fast, reliable, and human support every step of the way, so while Zown buyers of course praise the savings, just as regarded is the service they receive and the support they feel throughout the process.” Zown agents also have access to proprietary tools that include consolidated data on factors such as commute times, school ratings and crime statistics — features the company said give agents deeper insights to guide clients through buying or selling.
BCG’s Global Fintech Report says future growth is likely to come from fintechs in three emerging segments B2B(2X), Financial Infrastructure, and Lending
BCG’s Global Fintech Report says 2024 marked a turning point. Funding and valuations stabilized, and fundamentals improved sharply. Fintech revenues grew 21% year-over-year, up from 13% in 2023, and outpaced the 6% growth in the broader financial services sector. EBITDA margins for public fintechs increased by 25%, and 69% of them achieved profitability—up from less than half the year before. The first chapter of fintech produced scaled winners in digital wallets, acquiring, vertical SaaS, challenger banking, crypto trading, and BNPL. While a few players may still scale in these areas, these winners will be increasingly hard to displace. Future growth is likely to come from fintechs in three emerging segments:
B2B(2X). Businesses still face many pain points in payments, accounting, and treasury management—areas where AI can automate. Fintechs also still have much room for growth in embedding their solutions in SaaS platforms.
Financial Infrastructure. Though slower to scale due to longer sales and implementation cycles, the world’s financial infrastructure requires modernization to take advantage of technologies like AI and onchain finance.
Lending. Lending remains underpenetrated and ripe for innovation beyond unsecured consumer credit, especially in business and secured lending. As noted, new tailwinds are emerging that will support growth in this area.
Apple’s LLM for Siri with 150 billion parameters equals the quality of ChatGPT’s recent releases but shows higher levels of hallucination
A new report claims that internally, Apple has already been testing Large Language Models for Siri that are vastly more powerful than the shipping Apple Intelligence, but executives disagree about when to release it. Apple is said to be testing models with 3 billion, 7 billion, 33 billion, and 150 billion parameters. For comparison, Apple in 2024 said that Apple Intelligence’s foundation language models were of the order of 3 billion parameters. That version of Apple Intelligence is intentionally small in order for it to be possible to run on-device instead of requiring all prompts and requests to be sent to the cloud. The larger versions are cloud-based, and in the case of the 150 billion parameter model, now also said to approach the quality of ChatGPT’s most recent releases. However, there reportedly remain concerns over AI hallucinations. Apple is said to have held off releasing this Apple Intelligence model in part because of this, implying that the level of hallucinations is too high. There is said to be another reason for not yet shipping this cloud-based and much improved Siri Chatbot, though. It is claimed that there are philosophical differences between Apple’s senior executives over the release.
Microsoft proposes GenAI Intent-based routing (IBR)- Customer Intent Agent discovers and manages intents, while IBR uses those intents to route conversations, connecting customer needs to the right support resources with speed and precision
Intent-based routing (IBR) is a generative AI-powered capability that routes customer queries based on real-time intent recognition and dynamic user group assignment. It is enabled by the Customer Intent Agent, which autonomously discovers and manages customer intents by analyzing past interactions and builds an evolving intent library. Customer Intent Agent discovers and manages intents, while IBR uses those intents to route conversations, connecting customer needs to the right support resources with speed and precision. Once an intent and its group are identified, IBR routes the conversation to the appropriate user group based on the mapped intent group. Next, IBR assigns it to the best-suited support representative within the group, based on their capacity, presence, and other routing attributes. This enables faster, more accurate resolutions. By turning intent from a passive insight into an active, intelligent routing decision, IBR becomes the operational backbone of an intent-driven contact center. Subsequently, this results in better assisted and self-service experiences. Implementing intent-based routing in your contact center can offer numerous benefits: Enhanced precision and personalization; Dynamic intent discovery; Streamlined routing configuration; Smarter workforce management and load handling; and Scalable and adaptable.
Neema’s Dynamic Routing uses multiple real-time routes between countries and instantly analyses exchange rates, speed, and reliability for every cross-border transaction to identify the optimal route
Neema launched Dynamic Routing, an innovative technology designed to enhance every transaction by maximizing both success rates and cost efficiency. Neema’s extensive cross-border payments network empowers financial institutions across the globe to effortlessly process transactions in over 120 countries. It accommodates the most widely used payment methods and currencies specific to each destination, ensuring that users experience a localized payment environment. The introduction of Dynamic Routing further extends Neema’s vision of building a globally connected financial ecosystem. Dynamic Routing, along with Neema’s vast network of financial partners, enables a smarter method for global money movement. Rather than depending on a single pathway, Dynamic Routing establishes multiple real-time routes between countries. Each transaction it powers undergoes instant analysis, taking into account factors such as exchange rates, speed, and reliability to identify the optimal route. Every payment is personalized, with transfers between the same countries often utilizing different, optimized routes. Additionally, Neema’s AI-driven security infrastructure and expansive international reach provide enhanced visibility into coverage and technical vulnerabilities, allowing the company to effectively address potential gaps while offering one of the most robust quality assurance systems in the industry.
NMI offers Tap to Pay on iPhone for merchants that enables them to accept all forms of contactless payments using only an iPhone and a supporting iOS app without requiring additional hardware
NMI now enables its U.S. customers to seamlessly and securely accept in-person, contactless payments with Tap to Pay on iPhone. Tap to Pay on iPhone allows merchants to accept all forms of contactless payments, including contactless credit and debit cards, Apple Pay and other digital wallets, using only an iPhone and a supporting iOS app — no additional hardware or payment terminal needed. Using Tap to Pay on iPhone is easy, secure and private. With Tap to Pay on iPhone, at checkout, merchants simply prompt the customer to hold their contactless payment method near the merchant’s iPhone, and the payment is securely completed using NFC technology. Apple’s Tap to Pay on iPhone technology uses the built-in features of iPhone to help protect business and customer data. Apple doesn’t store card numbers on Apple servers, so merchants and customers can rest assured that their data stays theirs. NMI now offers two quick and easy options for enabling Tap to Pay on iPhone: NMI Tap to Pay iOS SDK empowers SaaS developers and fintech providers to embed Tap to Pay capabilities directly into their own iOS applications creating one seamless payment experience. The Cloud Commerce iOS app, powered by Mastercard’s Cloud Commerce solution (available soon on the Apple App Store), enables small businesses to quickly start accepting payments with just an iPhone, no new hardware required.
InvestorFlow AI private markets capital solution integrates seamlessly into firm-wide capital formation and deployment workflows, automatically extracting proprietary often unstructured data found in in firm-wide interactions and meeting notes
InvestorFlow, the AI-powered front-office solution for private markets, announced new AI capabilities that transform unstructured interactions into actionable insights for capital formation and deployment. InvestorFlow AI delivers game-changing outcomes: from the early access program with top private market firms, clients recorded a 15X increase in actionable insights, including critical KPIs and in-quarter deal opportunities, and a 10X improvement in data accuracy — turning data into advantage at AI-scale. InvestorFlow AI integrates seamlessly into firm-wide capital formation and deployment workflows, automatically extracting proprietary often unstructured data found in firm-wide interactions and meeting notes, enriching that information with industry data providers including Preqin and Pitchbook, and generating intelligent, dynamic briefs for every fund, investor or deal opportunity. These insights are embedded directly into existing pipelines and workflows, accelerating decision-making and productivity where users already work. InvestorFlow AI cuts through the complexity, rapidly surfacing the most strategic and actionable insights from vast amounts of unstructured data. Whether in private equity, venture capital, infrastructure, real estate or credit, capital allocators increase optionality and originate the best opportunities by synthesizing insights from their proprietary data. InvestorFlow AI helps by identifying investor preferences and investment targets, generating precision-targeted investor lists for investor relations leaders, streamlining meeting preparation and follow-up, and accelerating co-investment campaigns, all at an accelerated pace.