A major turf war is heating up in the payments worldand Visa and Mastercard suddenly find themselves on defense. Stablecoins like USDC are gaining traction, with companies like Shopify, Coinbase, and Stripe quietly rerouting payments around traditional card networks. For merchants, the pitch is irresistible: faster settlement, fewer fees, and no middlemen. With U.S. businesses spending roughly $187 billion a year on card swipe fees, even a small shift could redraw the map. Treasury Secretary Scott Bessent has hinted the stablecoin marketnow at $253 billioncould reach $2 trillion in the next few years. That’s not a side bet. That’s a direct hit. Visa and Mastercard aren’t sitting still. They’re flipping the narrativecasting themselves as the connective tissue for all things digital, stablecoins included. Visa is letting banks issue digital tokens and pilot stablecoin settlement directly on its network. Mastercard, meanwhile, just teamed up with Paxos to mint and redeem USDG, its fiat-backed stablecoin. The two networks are leaning into their edge: global scale, trusted rails, built-in fraud protection, and tokenization tech that masks sensitive data at checkout. That’s not just defense. It’s a strategic pivot.
Survey finds Gen Z and Millennials are the most likely to double-check AI-generated responses, with fact-checking rates of 47% and 44%, respectively indicating trust is a challenge when using gen AI
Coveo Solutions Inc.‘s latest Employee Experience Relevance Report found that nearly half of the employees feel frustrated when they don’t have access to the right tools or information. Frustration related to unhelpful tools has only increased over the past few years, from 28% in 2022 to 40% in 2025. Meanwhile, confidence has dropped. These frustrations are part of a broader problem. Information is scattered across too many systems. The same tools that organizations have put in place to fix disconnected systems are still ineffective in many cases according to the employee feedback from the survey: including intranets (31%), enterprise search tools (24%), and generative AI (15%). When using gen AI, trust is a challenge. 42% of employees fact-checked answers provided by AI tools in 2025, up from 36% in 2024. Trust is only slightly higher in enterprise-approved tools than in open-source tools like ChatGPT, with just 17% of employees fully trusting responses from internal systems and 14% trusting open-source tools. Gen Z and Millennials are the most likely to double-check AI-generated responses, with fact-checking rates of 47% and 44%, respectively. Nearly half of the respondents experienced a hallucination when it comes to using AI, with 22% saying it happened during work. These aren’t limited to minor issues either. They’re happening in core business functions such as software development, IT and executive leadership. Weekly hallucinations were reported by 60% or more in each group. Hallucinations are also prevalent in industries with quick decision-making, such as software, IT, finance and accounting. AI hasn’t delivered on the promise of reducing the time it takes to find information. Employees are still moving among multiple systems and sources to search for information needed to do their job. Those in tech roles navigate five or six systems on average. The findings suggest that many AI deployments are still more customer-focused than employee-facing. Employee productivity is lower on the list at 26%. Across large organizations, looking for information amounts to millions of hours wasted each year. It’s clear from the report findings that current systems aren’t helping people focus as they should. The hope is that gen AI could turn things around. According to 42% of the employees surveyed, their organizations have already invested in gen AI tools and training aimed at improving information search in the workplace.
Genesis AI’s AI models for smart robotics adopt a data-centric, full-stack approach to physical AI by developing a scalable universal data engine for physics simulation to build robots that can work around people, adapt and overcome complex spaces and even understand new situations
Genesis AI, a global physical artificial intelligence research lab that develops AI models for smart robotics, has launched after raising $105 million in funding. Genesis AI said that it brings a data-centric, full-stack approach to physical AI by building a scalable universal data engine for physics simulation and using large-scale robotics data collection. Robots driven by physical AI robotics foundation models, or RFMs, can work around people, adapt and overcome complex spaces and work alongside people and even understand situations they were not originally introduced to. Genesis said it wants to deliver a platform that can bring human-level intelligence to robotics for different robots with an RFM that can be deployed no matter the type of robot. To approach the matter, the company forged an expert team of industry technical talent and academia from Mistral AI SAS, Nvidia Corp., Google LLC, Carnegie Mellon University, Massachusetts Institute of Technology, Stanford University, Columbia University and the University of Maryland. Genesis said its core engineering team has deep expertise in simulation, graphics, robots and large-scale AI model training and deployment. Genesis believes there’s a clear opportunity for general-purpose robotics across factory floors, warehouses, healthcare and agriculture. All these scenarios require precise tool use and close proximity with human counterparts, which cannot be easily programmed with the current software stacks employed by modern solutions.
Regulatory acceptance of digital currencies similar to MiCA-compliant stablecoins could create interoperable frameworks that can preserve monetary sovereignty while benefiting from more liquid, efficient settlement rails
Observers across financial, regulatory, and crypto communities saw in MiCA the early contours of a potential digital euro—and a precedent that could influence global standards. Now, with the rules officially in effect for stablecoins as of June 2024, their regulatory acceptance is no longer theoretical. Across the EU, MiCA-compliant stablecoins are circulating in volume. These include Dutch-issued euro stablecoins, U.S.-based euro tokens, decentralized versions like Euro Tether, and dollar stablecoins restructured to meet MiCA’s requirements. Because global liquidity is incredibly helpful—especially when it’s programmable, transparent, and accessible across borders. In the six months following MiCA’s implementation, regulators in several jurisdictions have taken concrete steps to define their own approaches to stablecoins. In July 2024, Singapore finalized its Stablecoin Regulatory Framework, which includes capital and redemption safeguards, similar to MiCA’s EMT structure. The United States remains slower to move. The Clarity for Payment Stablecoins Act of 2023 is still stalled in Congress, though the New York Department of Financial Services has taken the lead by issuing individual approvals for USD-backed stablecoins. Meanwhile, Hong Kong concluded its stablecoin consultation in early 2025, signaling a shift toward regulatory recognition in Asia. If countries recognize each other’s regulated digital currencies—or better yet, create interoperable frameworks—they can preserve monetary sovereignty while benefiting from more liquid, efficient settlement rails.
Modernizing existing REST APIs requires identifying APIs with OpenAPI specs, evaluating which APIs you want AI agents to have access to, configuring the MCP server, handling authentication and authorization, and deploying using the sidecar pattern
This blog discusses how organizations can modernize existing REST APIs with minimal effort by exposing them as tools via the Model Context Protocol (MCP). MCP is a universal standard that allows AI models to interact with external tools, data sources, and applications, effectively serving as a bridge between AI systems and the broader digital ecosystem. To modernize existing REST APIs, follow a 4-step process: Understand your application’s API surface: Use a well-documented REST API with an OpenAPI specification; Wrap your API with FastMCP: FastMCP is a lightweight server that automatically converts API endpoints into tools that AI agents can understand and call; Deploy both your existing application and the MCP server together using Amazon Elastic Container Service (Amazon ECS) and AWS Fargate with a sidecar pattern; Build the AI agent with Strands Agents SDK: Strands provides a clean interface for connecting to MCP servers and integrating with Amazon Bedrock. To adapt this pattern for your existing applications, identify APIs with OpenAPI specs, evaluate which APIs you want AI agents to have access to, configure the MCP server, handle authentication and authorization, deploy using the sidecar pattern, and test and iterate. Benefits of this approach include minimal changes to existing applications, incremental modernization without a complete rewrite, scalable architecture, security by design, and cost-effectiveness. To get started with modernizing your own applications, review the Strands Agents SDK documentation, explore Amazon Bedrock for available AI models, identify applications with well-documented REST APIs, start with a proof of concept using a non-critical application, consider authentication and security requirements for production deployment, and limit API endpoints the agent has access to through FastMCP configuration options.
Stablecoins could destabilize the global payment system by creating a dollar-alternative and becoming “quasi-banks”, letting people deposit money in a stablecoin and assume they can withdraw it at any time
Asset manager Amundi has raised concerns that a boom in dollar-backed stablecoins in the wake of the United States’ GENIUS Act could cause a major shift in money flows that destabilises the global payment system. “It could be genius, or it could be evil,” Amundi Asset Management’s chief investment officer Vincent Mortier told, voicing his concerns about the U.S. act. JPMorgan expects the amount of stablecoins in circulation to roughly double to $500 billion in the next few years, although some estimates have put it as high as $2 trillion. As stablecoins need be pegged to the dollar under the U.S. act, it will trigger buying of U.S. Treasury bonds. That has its benefits for the U.S. as it grapples with a gaping budget deficit, but could also pose problems for the U.S. and other countries. “In doing so you create an alternative to the U.S. dollar and that could lead to more weakening of the dollar,” Mortier said. “Because if a country is pushing a stablecoin, it could be perceived as pushing the message that the dollar is not that strong.” Currently, 98% of all stablecoins are pegged to the dollar, but more than 80% of stablecoin transactions happen outside the United States. Mortier said he still had not fully made up his mind about stablecoins, but the worry was that a mass uptake could impact financial stability. As well as the dollarization issue, they would become “quasi-banks” he said, as people will deposit money in a coin assuming they can take it out again whenever they want. They will also be used as a direct means of payment.
JPMorgan names a global head for its private bank, to offer cross-border investment advice, access to fast-growing private markets and help navigate risks tied to conflicts and trade disputes
JPMorgan Chase reportedly reorganized its private bank and named a global head of the bank, which is a new role. David Frame, who previously served as the U.S. head of the private bank, has been appointed to the new role. The reorganization of the private bank and the creation of the new role are meant to help the bank assist its wealthy customers in storing their money around the world. Previously, the private bank focused on clients in individual countries. The private bank requires a minimum balance of $10 million and has found that these wealthy individuals want to diversify their investments rather than keeping their assets in a single country or region. While there has long been demand for this sort of diversification, it has been accelerated by concerns about issues like global conflicts and trade tensions. In another effort focused on wealthy customers, JPMorgan Chase said in May that it is accelerating the rollout of the affluent banking offering it introduced late last year. After opening two J.P. Morgan Financial Centers in late 2024, the bank said it would add 14 more in May and would have 31 in operation by the end of 2026. This branch format is designed to cater to the needs of affluent clients by providing private meeting spaces, distinctive finishes, personalized support from a dedicated senior private client banker and a full range of banking and wealth management offerings.
KeyBank deepens its collaboration with Qolo- platform for card issuing, ledger management, and payment processing- allowing to add same-day ACH reconciliation, advanced dashboard reporting, and simplified statement reporting, which have improved the platform’s functionality and customer experience
The KeyBank-Qolo alliance reflects an evolution in how banks and fintechs can co-create value through deeper integration. Qolo is an all-in-one platform for card issuing, ledger management, and payment processing, designed to simplify and streamline your operations. The partnership has allowed KeyBank to add features like same-day ACH reconciliation, advanced dashboard reporting, and simplified statement reporting, which have improved the platform’s functionality and customer experience. The collaboration between the two firms goes beyond a typical vendor-client relationship, with both companies working closely on product development and infrastructure investments. The decision-making process for such partnerships at KeyBank involves considering factors like time to market, alignment with core competencies, regulatory complexity, total cost of ownership, and strategic control. The success of the KeyBank-Qolo partnership is attributed to factors like foundational business model alignment, cultural alignment, and deep technical integration. What sets this partnership apart is the shared ability to co-build and influence the evolution of embedded banking infrastructure together, according to Bennie Pennington, Head of Embedded Banking at KeyBank. Pennington noted that KeyBank’s operational depth — spanning the nuance of regulation, risk management, and customer workflow patterns — complements Qolo’s speed and technical flexibility, creating a joint capability greater than the sum of its parts. KeyBank’s core banking systems must connect smoothly with Qolo’s infrastructure, which handles transaction data but also sends near real-time updates on risk, compliance, and operational metrics, backed by redundant data flows. To achieve this level of coordination, KeyBank has configured its integration so that Qolo can receive payment settlement requests directly from its ACH settlement platform. Embedded banking infrastructure falls into what Pennington refers to as “specialized table stakes”: essential for all players, but not a space where banks can typically differentiate. Qolo’s tech gives the bank a competitive edge by focusing on implementation and customer experience, instead of relying on exclusivity.
Brex uses a “superhuman product-market-fit test” to figure out what tools are worth investing in beyond the pilot program
Brex completely changed its approach to software procurement to ensure it wouldn’t get left behind. Brex CTO James Reggio told that the company initially tried to assess these software tools through its usual procurement strategy. The startup quickly discovered its months-long piloting process was just not going to work. The company started by coming up with a new framework for data processing agreements and legal validations for bringing on AI tools, Reggio said. This allowed Brex to vet potential AI tools more quickly and get them into the hands of testers faster. Reggio said the company uses a “superhuman product-market-fit test” to figure out what tools are worth investing in beyond the pilot program. This approach gives employees a much larger role in deciding what tools the company should adopt based on where they are finding value, he added. “We’re basically, I would say, about two years into this new era where there’s 1,000 AI tools within our company. And we’ve definitely canceled and not renewed maybe five to 10 different larger deployments.” “By delegating that spending authority to the individuals who are going to be leveraging this, they make the optimal decisions for optimizing their workflows,” Reggio said. This approach has helped the company figure out where it needs broader licensing deals for software too based on a more accurate headcount of how many engineers are using what.
Wells Fargo financial scandal in 2016 diminished consumer trust in traditional banks while driving homebuyers to fintech lenders for mortgages, study suggests
The Wells Fargo financial scandal in 2016 diminished consumer trust in traditional banks while driving homebuyers to fintech lenders for mortgages, a University of California, Davis study suggests. The paper was written by Keer Yang, an assistant professor in the UC Davis Graduate School of Management specializing in finance and financial technology. The difference in interest rates and other fees for comparable 30-year, fixed-rate loans on single-family homes between banks and fintech lenders did not change after the 2016 scandal. “Therefore, it is trust, not the interest rate, that affects the borrower’s probability of choosing a fintech lender,” Yang wrote. Yang analyzed Gallup poll answers regarding trust in banks, internet searches on Google Trends on bank scandals, newspaper articles about the Wells Fargo fines and scandal, and deposits and mortgage loan data sets in traditional banks and in fintech lenders. The period examined was 2012 to 2021. Use of financial services increased from 2% of the market in 2010, before any knowledge of the Wells Fargo scandal, to 8% in 2016, according to the research paper. Furthermore, in areas with Wells Fargo banks—where exposure to the scandal was more pronounced—customers were on average 4% more likely to use non-bank lenders than any banks after 2016. The scandal had a minimal effect on bank deposits, probably because of the protections afforded by deposit insurance, Yang said.