VantageScore successfully completed two independent pilot programs using VantageScore 4plus™, the newest VantageScore credit scoring model leveraging the power of industry-leading VantageScore 4plus™ alternative open banking data. Pilots conducted with Patelco Credit Union and Michigan State University Federal Credit Union (MSUFCU) each demonstrated significant quantitative improvements in credit risk prediction, as well as a significant expansion in access to credit for underserved consumers. “These results show that open banking data, when used responsibly and in combination with credit file data, can dramatically improve both risk management and financial inclusion,” said Dr. Andrada Pacheco, Executive Vice President and Chief Data Scientist at VantageScore. The solution builds on the industry-leading performance of the VantageScore models by adding bank transaction data to deliver a real-time, FCRA-compliant credit score. It offers enhanced risk separation among populations with limited credit histories, according to analyses performed by VantageScore. Because it is compatible with all three major credit bureaus and aggregator APIs, lenders can easily adopt it without overhauling credit policies. Michigan State University Federal Credit Union saw strong results in VantageScore 4plus™ testing, including: 33% of subprime moved to higher credit tiers; 41% of near prime members moved to higher credit tiers. In testing its portfolio, Patelco Credit Union found that VantageScore 4plus™ delivered: 12% of subprime and 15% of near prime members moved to higher credit tiers; 4.8% improvement in predictive power over VantageScore 3.0 in originations
iOS 26 Beta 2 improves the readability and differentiation of Control Center on Liquid Glass by adjusting the background blur, which better obscures the Home Screen content underneath
With the release of iOS 26 Beta 2, Apple has fixed one of the more glaring issues with Liquid Glass. The refreshed user interface modernizes the operating system’s look and feel with a design system inspired by the optical qualities of glass, including the way it refracts light and its translucency. One of the users’ larger concerns was with how Liquid Glass made the Control Center (the menu accessed by swiping down on the right side of the iPhone’s screen) nearly unreadable. Because of its semi-transparent nature, it was hard to differentiate the Control Center’s buttons and sliders from the icons and widgets on the iPhone’s Home Screen that appeared underneath. In the newly released beta, Apple has addressed the problem with the Control Center by adjusting the background blur, which better obscures the Home Screen content underneath. Notifications in the first beta were also hard to read, as many had pointed out. In the updated beta, they’re a bit sharper but still need work, especially for readability on brighter and lighter backgrounds. Also in Beta 2, Apple has added an Accessibility section to the App Store’s product pages, enabled iCloud sync for the Journaling app on iPads, added order tracking features to Apple Wallet, introduced an Apple Music Radio widget, and more.
J.D. Power’s study finds banking virtual assistants are not as much of a differentiator anymore in boosting customer satisfaction as consumers getting used to more versatile GenAI assistants
Virtual assistants aren’t providing the boost in customer satisfaction that they once did, according to analysis across the firm’s banking and credit card mobile app studies. The average percentage of responding consumers who used a virtual assistant actually fell from 33% to 30%. The average overall satisfaction among consumers who used a virtual assistant also fell, from 691 to 687. Sean Gelles, senior director of banking and payments intelligence, believes the reason behind these declines goes beyond the virtual assistants themselves, which major institutions have been developing continuously. He points to OpenAI’s ChatGPT, Microsoft Copilot, Meta AI and other GenAI tools. Virtual assistants have been looked to as the next step up. But consumers are getting used to more versatile GenAI assistants like ChatGPT and Copilot. He believes things are getting to the point where virtual assistants that were good — or good enough — in the past are not as much of a differentiator anymore. J.D. Power’s analysis found that customer satisfaction with apps and sites has been improving, but chiefly because of increased speed and other technical enhancements. Gelles says institutions have to begin assessing what’s missing from their digital experiences in general, as well as how GenAI could potentially improve their offerings. Overall, ease of use of digital channels remains a sticking point for customer satisfaction, according to Gelles. He says the average across the studies for users saying that they find the tools easy to use is only 28%. In a financial context, instead of presenting static choices, Gelles says, financial players could personalize things from the get-go, drawing on what services the consumer has tapped before.
Microsoft’s new small language model can run locally on Windows 11 PCs using encoder-decoder approach that reduces AI compute cycle, breaking down large queries into more compact representation
Microsoft has announced a small language model called Mu, which will enable the running of generative AI (genAI) agents on Windows without internet connectivity. Mu uses the neural processing units (NPUs) of Copilot PCs, which are provided by three chip makers — Intel, AMD, and Qualcomm. The model provides a better understanding and context of queries and is designed to operate efficiently, delivering high performance while running locally. Microsoft is pushing genAI features into the core of Windows 11 and Microsoft 365, introducing a new developer stack called Windows ML 2.0 last month for developers to make AI features accessible in software applications. The 330-million parameter Mu model is designed to reduce AI computing cycles so it can run locally on Windows 11 PCs, as laptops have limited hardware and battery life and need a cloud service for AI. The model also generates high-quality responses with a better understanding of queries. The encoder-decoder model breaks down large queries into a more compact representation of information, which is then used to generate responses. The encoder-decoder approach is significantly faster than large language models (LLMs), such as Microsoft’s Phi-3.5, which is a decoder-only model.
Google Pay’s integration with Klarna allows users to easily set up a “Pay Later” schedule for purchases over $35 through pop-ups on Android and other platforms
If you’ve used Google Pay at all in recent weeks, you’re probably more than familiar with the “Pay Later” functionality that has recently rolled out. Now, Klarna and Google Pay have officially announced the functionality. “Buy Now, Pay Later” programs have become extremely common over the past few years, with many retailers allowing customers to split up their payments over the course of a few weeks or months to make the purchase a bit more flexible. There are a bunch of different companies powering this, with Klarna being one of the biggest names (and one of the only ones soon to be a mobile carrier too). In a press release this week, Klarna has officially announced its new integration with Google Pay. Through Google Pay pop-ups on Android and other platforms, users can now easily set up a “Pay Later” schedule with virtually any purchase as long as it’s over $35. Klarna explains: Klarna, the global digital bank and flexible payments provider, is now available as a payment option on Google Pay. Shoppers can use Klarna’s flexible payment options online on select Android apps and websites that offer Google Pay at checkout. By joining forces with one of the most widely used digital wallets in the country, Klarna continues to accelerate its growth in the U.S. market. This integration builds on Klarna’s commitment to responsible spending and empowers consumers with more choices in how they shop. Klarna’s Pay in 4 payment offering gives consumers four fixed repayments for purchases over $35, all interest-free. Financing is available for higher ticket items with monthly repayments made over a longer period of time starting at 0% APR. As mentioned, you’ve probably seen this already. Google Pay has been showing this new “Pay Later” functionality prominently, almost to an annoying degree every time an Android user is going through a purchase as of late. “Pay Later” functionality has been available in Pay for a while now, with Affirm and Zip both having been added in 2023. Afterpay was also added in 2024. Ironically, though, we didn’t see Klarna while testing out the “Pay Later” functionality, so it does still seem to be rolling out.
Plaid offers easy connect to its apps via Ozone API enabling American FIs to launch secure, scalable, and standards-compliant API services faster than ever
Ozone API, announced a new partnership with Plaid. As part of the collaboration, Ozone API will join Plaid’s FDX-enabled Gateway Partner Program, bringing Ozone API’s powerful open banking platform to Plaid’s network of over 12,000 financial institutions and 8,000 fintechs across North America and beyond. Through the partnership, the Ozone API platform provides this API as a seamless, out-of-the-box integration with Plaid’s infrastructure, enabling customers of banks and financial institutions to seamlessly connect to thousands of apps on the Plaid network. The collaboration reflects a shared commitment to innovation, regulatory compliance, and enhanced customer value within the rapidly evolving financial landscape. Through this partnership, financial institutions will be able to harness the full potential of open banking, driving new avenues for growth, enriching customer experiences, and exploring innovative embedded financial services. Huw Davies, Co-Founder & CEO of Ozone API said “By joining Plaid’s Gateway Partner Program, we can significantly accelerate open banking adoption across North America. This partnership empowers financial institutions to launch secure, scalable, and standards-compliant API services faster than ever, marking a major step forward in delivering true open finance and tangible commercial impact.”
Study shows 43% of retailers find handling online order returns in-store is a top challenge as store design is not adapted for it and increases in the volume of returns has created new costs
Forty-three percent of retailers say handling online order returns in-store is a top challenge, and that increases in the volume of returns has created new costs, according to a new study from Retail Systems Research (RSR), sponsored by retail technology provider Jumpmind. More than one-in-five retailers told RSR their stores were not designed for today’s more advanced customer service functions, such as order pickup, online returns, etc. Forty-one percent said that omnichannel fulfillment and returns require new in-store sales rep roles and workflows. RSR noted that the average return rate for online transactions is three-times higher than the return rate for in-store purchases. Despite challenges, 72% of retailers surveyed believe in-store returns can create opportunities to drive new sales. However, only 17% of shoppers end up spending more money following a return in-store. The vast majority of consumers surveyed (43%) simply return the item and walk out, revealing that retailers have a long way to go in improving the process.
Spreedly integrates Just-In-Time Card Updates for Visa Cards to provide merchants with up-to-date and real-time access to refreshed card credentials at the point of transaction using Open Payments Platform
Spreedly announced a strategic enhancement to its platform through the integration of Just-In-Time Card Updates for Visa Cards powered by Visa Account Updater (VAU). Spreedly’s Just-In-Time Card Updates integration provides merchants with up-to-date card credentials precisely when they’re needed. Unlike traditional card update strategies, which operate on a scheduled batch basis, Just-In-Time Card Updates enable real-time access to refreshed card credentials at the point of transaction to give merchants greater control and responsiveness. Built on the Advanced Vault capabilities of the Open Payments Platform, Spreedly leverages Visa’s powerful network to give merchants control to fetch card updates at the right place and right time. This ability to leverage tools on demand allows businesses to better manage their operational costs and prevent disruption to the customer experience for card-on-file and subscription payments. In addition to integrating with VAU to enable Just-In-Time Card Updates, Spreedly is integrating Visa Acceptance across key gateways—including CyberSource and Authorize.Net—to provide merchants with greater reach and reliability. Key Business Benefits: Improved Authorization Rates: Reduce declines caused by outdated card credentials and recover revenue from failed transactions. Operational Efficiency: On-demand updates eliminate the need for constant background refreshes; this streamlines payment workflows and reduces costs. Customer Retention: Prevent service interruptions and improve customer loyalty by ensuring seamless, uninterrupted transactions. Strategic Flexibility: Merchants control the timing and use of card updates, aligning payment operations with business needs.
Algebrik AI’s integration with TruStage platform is to enable FIs to present lending protection products directly within the digital loan application flow
Algebrik AI announced a partnership with TruStage™, to integrate the education of a broad suite of lending protection offerings from TruStage—including GAP coverage, debt protection, credit insurance, and mechanical repair coverage—directly into Algebrik’s end-to-end digital lending workflows. With this integration, Algebrik enables credit unions and community lenders to present TruStage protection products directly within the digital loan application flow—empowering borrowers to choose coverage that fits their needs without disrupting the journey. Whether for auto loans, personal loans, or other credit products, protection options are embedded natively into Algebrik’s borrower experience and remain easily configurable by loan officers. Key Benefits of the Integration: Comprehensive Coverage Options – Offer GAP coverage, credit insurance, debt protection, and mechanical repair coverage products—all surfaced directly within Algebrik’s LOS. Embedded at the Point of Decision – Borrowers encounter relevant protection choices within the same digital flow, with no need to redirect or re-engage later. Configurable by Loan Type & Member Segment – Institutions can tailor which TruStage products are presented based on loan type, member profile, or risk category. Simplified Operations, Centralized Reporting – Built-in tracking, configuration, and compliance support helps lenders manage enrollment, documentation, and servicing with minimal manual effort.
Mastercard said it is expanding its First Party Trust program to tackle “friendly” fraud- genuine transactions that are challenged by cardholders, to assist businesses in researching and addressing claims
Mastercard said it is expanding its First Party Trust program to tackle “friendly” fraud. Also known as first-party fraud, the term refers to genuine transactions that are challenged by cardholders, whether it’s deliberately or happens by mistake. eCommerce has revolutionized the transaction experience while also increasing the need for transparency of payments for merchants, small business owners and entrepreneurs. It is now easier than ever for a customer to dispute a debit or credit card transaction they don’t recognize. The card issuer must then determine whether to provide that cardholder with a refund for the transaction amount — this is known as a chargeback. The global cost of chargebacks to merchants is projected to rise to $42 billion by 2028, with almost half of those transactions being reported as fraudulent. To help deal with this issue, Mastercard says it is expanding its First-Party Trust program, introduced in 2023, to Canada, Latin America, the Caribbean and across the Asia Pacific region. The program assists businesses both big and small with burdensome time and resource-intensive issues, such as researching and addressing claims. It provides enhanced data-sharing, either at the time of transaction or at the time a dispute is raised. Issuers can better identify third-party fraud, where someone’s details are used without consent, from first-party fraud and gain reliable information to resolve cardholder disputes.