OpenAI’s integration with Shopify is expected to revolutionize online shopping, transforming the internet into a more personalized experience. The integration will allow digital personal shoppers to know customers’ size, style, and preferences, allowing them to make more informed decisions about their purchases. This could lead to a shift from traditional storefronts to full-service consultants and lifestyle experts. The adoption of Gen AI will result in lower return rates, reduced bounce rates, and a rise in’shopper loyalty’ as consumers build an affinity with stores that make their lives easier and feel special. To optimize the integration, brands should focus on user-generated content, build a real community, and train their assistants cleverly. The partnership between OpenAI and Shopify could mark an unprecedented step forward in using Gen AI as a shopping tool. By integrating product details, pricing, reviews, and even a ‘Buy Now’ button directly into the UI, the future of online shopping will be significantly changed. The winners will be those that think beyond the transaction and create experiences that feel truly personal.
Google Desktop Chrome is using the on-device Gemini Nano model to provide instant insight on risky websites and an additional layer of defense against undetected scams
Google published a report about how it’s using the latest AI approaches to combat spam across Search, Chrome (with Gemini Nano for Enhanced Protection), and Android. Google Search credits AI-powered scam detection systems as currently helping detect and block “hundreds of millions of scammy results every day.” The company notes how it can now “analyze vast quantities of text and identify subtle linguistic patterns and thematic connections that might indicate coordinated scam campaigns or emerging fraudulent narratives.” In addition to the “Standard Protection” warnings when you come across a nefarious site, Safe Browsing offers an optional “Enhanced Protection” mode against phishing and other scams. Desktop Chrome is now using the on-device Gemini Nano model to “provide Enhanced Protection users with an additional layer of defense against online scams.” The LLM “provides instant insight on risky websites and allows us to offer protection, even against scams that haven’t been seen before.” Google is already using this to “protect users from remote tech support scams,” with plans to cover more types and bringing to the Android browser in the future. Meanwhile, Chrome for Android will use an on-device machine learning model that flags “malicious, spammy or misleading notifications” and labels them as “Possible scam.” Users can “Show notification” or “Unsubscribe.”
Pagaya’s platform for second-look personal loans offers potential for a mid-sized bank of over $1.5 billion of personal-loan origination in less than nine months; can help lenders “bid better” on Credit Karma or Experian
Alternative lending fintech Pagaya Technologies has its sights set on expanding its personal loan offering to regional and super-regional banks while it also builds out its marketing acquisition engine. Pagaya currently partners with banks such as U.S. Bank and neobanks such as SoFi to offer artificial intelligence-powered second-look personal loans to consumers who might not otherwise qualify. Pagaya integrates with lenders’ loan origination systems and buys the loans it originates from the lenders and sells those loans on the secondary market. It is also active in auto lending and point-of-sale buy now/pay later lending. All in, Pagaya counts 31 lenders as partners. Pagaya is in talks with four or five regional banks to help build out or expand their personal-loan offerings, co-founder and CEO Gal Krubiner told. “There is a new era where people are starting to look at growth, and for the regional banks, personal loan is a good way to grow the franchise and to give solutions and products to their customers,” he said. Many regional banks look to personal loans to help secure deposit inflows, a trend that Pagaya is hoping to capitalize on when bringing new partner banks into the fold, Krubiner said. “From our perspective … working with Pagaya could generate for a mid-sized bank over $1.5 billion of personal-loan origination in less than nine months,” Krubiner said, citing U.S. Bank’s performance on the platform. Pagaya is also using its integration into lenders’ underwriting platforms to offer pre-screened loans to potential customers in another avenue that it hopes will lead to growth, said Sanjiv Das, president of Pagaya. “Think about our total market opportunity. We have 31 lending partners. Those 31 lending partners have about 60 million consumers as existing customers. We’ve only scratched the surface right now with the 3% [penetration],” Das, told. Pagaya is also working to help lenders “bid better” for leads from data aggregators, such as Credit Karma or Experian, Das said. The push toward regional banks comes on the heels of solid first-quarter earnings results that beat analysts’ estimates across nearly every metric. Revenue jumped 18% year over year to $290 million, ahead of analysts’ expected $285 million. Net income landed at $8 million, or 10 cents per share, compared with a $21 million loss in the same reporting period last year and eclipsing analysts’ estimate of a $10 million, or 15 cent per diluted share, loss. Shares of Pagaya have risen about 26% since the company reported earnings on May 7, according to a research note from David Scharf at Citizens. Scharf attributes the gains to Pagaya hitting positive GAAP net income ahead of schedule. KBW analyst Sanjay Sakhrani bumped his price target for Pagaya’s stock following the earnings report, pointing to pre-screen and affiliate channels as “growth drivers.” “We believe PGY is well-positioned to shift toward revenue growth across its three loan markets — personal, auto, and POS and deliver profitability. While macroeconomic volatility may introduce risks to funding costs and underwriting capabilities, management’s disciplined risk approach and measured appetite provide confidence,” Sakhrani said.
Au10tix’s API for real-time AML risk monitoring dynamically adjusts the intensity of screening processes through proactive scanning of over 100 global sanctions lists, PEP databases, and adverse media
AU10TIX has launched continuous risk monitoring as part of its advanced AML solution. Driven by customer demand, this powerful capability delivers real-time risk insights across the full customer lifecycle—empowering businesses to detect behavioral anomalies and emerging threats as they arise. AU10TIX’s continuous monitoring capability proactively scans top data sources including global sanctions lists, politically exposed person (PEP) databases, and adverse media in real time to detect anomalies as they emerge. The system dynamically adjusts screening intensity based on customer risk profiles and business requirements—supporting KYC and KYB processes while ensuring adherence to evolving global regulations. AU10TIX’s AML solution features a proprietary decision-making mechanism, customizable workflows, and a user-friendly dashboard to streamline risk management and due diligence processes. The new capability provides: Real-time fraud and money laundering alerts; Adaptive risk scoring, continuously recalibrated based on real-time data and changing user behavior; Flexible thresholding tailored to customer risk levels; Coverage across 240+ countries and 1,600 government sites; A unified dashboard for identity verification and AML results; and Seamless KYC + KYB support in a single compliance flow
Cardlytics solution allows any merchant with digital channels and a loyalty program to become a publisher on its platform and roll out targeted card-linked offers targeted on purchase data from a third-party vendor
Cardlytics announced the general availability of Cardlytics Rewards Platform (CRP), a new solution that provides publishers the opportunity to enhance their customer loyalty programs with card-linked offers. With CRP, a merchant with digital channels and a loyalty program can now become a publisher on the Cardlytics network and offer more value to their customers. This opens up Cardlytics’ supply to new verticals beyond financial services – such as retail and restaurants – and provides advertisers increased exposure, reach and engagement with consumers where they are already transacting. Publishers can also boost engagement with their customers by incentivizing them to earn rewards on their purchases and improving the shopping experience, helping to create a flywheel for CRP partners. CRP is an extension of Cardlytics’ core platform for financial institution partners, with the same advertiser offers flowing seamlessly to new publisher channels. Offers on CRP are delivered within a publisher’s loyalty program and targeted based on purchase data from a third-party vendor. After opting in to receive offers and connecting their bank account information, customers can activate offers and earn rewards in the form of the publisher’s loyalty currency, such as points or loyalty cash, which can be used for future purchases. Amit Gupta, CEO of Cardlytics said “By enabling our advertisers to become publishers, we are unlocking new opportunities for growth and redefining what it means to be a partner in our ecosystem.”
Curve Pay launches on iOS as Apple Pay alternative; to leverage iPhone NFC feature to offer more than tap-to-pay experience that includes split payments, rewards stacking and real-time spending
Curve announced the launch of Curve Pay on iOS, the first payment solution to leverage the newly accessible iPhone NFC interface after Apple’s acceptance of the European Commission’s ruling. As a staged wallet with built-in smart features — including real-time spending insights, the ability to switch payment sources post-transaction, and rewards stacking — Curve Pay gives iOS users more functionality than ever before. Now with Apple’s hands forced to open to competition, Curve Pay ushers in a new era of choice for iOS consumers,” said Shachar Bialick, CEO & Founder of Curve. “With Curve Pay also recently going live on Android, we are bringing universal access to all Curve users, regardless of device — so everyone can now manage their money, on any phone, with all the unique Curve benefits that comes with it.” Unlike pass-through wallets like Apple Pay, which simply transmit existing card credentials, Curve’s staged architecture means it actively sits in the payment flow. That allows Curve to offer far more than a tap-to-pay experience. Customers can retroactively change the card they used, split payments, earn cashback, track spending in real time and even pay from accounts like PayPal — all through a single app.
PlainID’s Policy Management for Agentic AI allows organizations to define dynamic, fine-grained policies that apply adaptable controls to every AI Agent interaction with data, APIs and services
PlainID, global provider of Identity Security, introduces Policy Management for Agentic AI. Policy Management for Agentic AI enables organizations to define granular policies that control what data AI agents can access, how they process it, and which actions they may take—ensuring that every AI-driven workflow abides by corporate and regulatory mandates. Key capabilities include: Identity-aware control – Enforce access based on human and non-human identity (NHI). Dynamic, fine-grained policies – Apply adaptable controls to every AI Agent interaction with data, APIs and services. Centralized policy management – Manage and govern all policies in one unified, standardized interface. Seamless integration – With popular AI platforms and orchestration frameworks Zero Trust Alignment – Ensure AI operations align with enterprise security and compliance frameworks, by design. Auditability – Gain full visibility into AI decision chains, access attempts, and policy outcomes. “As enterprises accelerate AI initiatives, PlainID empowers teams to govern AI data and decisions without compromising innovation. Through policy management and access enforcement, we ensure every AI interaction is secure, compliant, and policy-aware,” said Gal Helemski, Chief Product Officer and Co-Founder of PlainID.
Pegasystems Agentic Process Fabric leverages Pega’s existing Process Fabric architecture to coordinate tasks across applications while ensuring agents operate in line with business goals
Workflow automation firm Pegasystems will announce what it calls a major extension of its artificial intelligence automation capabilities. The announcements center on Pega Agentic Process Fabric, a new orchestration service designed to unify AI agents across an enterprise. The Pega Blueprint workflow design platform is also getting improved integration with legacy information. Agentic Process Fabric connects AI agents with existing business systems, data and workflows. The system leverages Pega’s existing Process Fabric architecture to coordinate tasks across applications while ensuring agents operate in line with business goals and compliance standards. “Agentic Process Fabric… allows enterprises to build a registry of all of their workflows, existing systems, existing applications, all of their AI agents — both Pega’s and non-Pega’s — and stitch everything together into a unified agentic experience,” said Matt Healy, senior director of product strategy and marketing at Pegasystems. Pega’s design separates AI usage into two distinct phases: design-time and runtime. The design stage uses AI reasoning to create new workflows, while semantic AI handles execution. Pega said the combination is intended to reduce the risk of erratic agent behavior. The platform enables users to interact with agents via chat interfaces, email, voice assistants and other channels. The system dynamically selects and engages the most appropriate agents and workflows for each task based on available data and user input. It also supports on-the-fly workflow generation through Blueprint design agents. New features in the Pega Blueprint platform are aimed at streamlining the inclusion of legacy content in re-architected workflows.
Uber adds a new type of account with a simpler UI for the elderly with features like ride updates for family members, saved destinations, and the ability to use a family member’s card for payments
Uber revealed a new type of account, called Senior Accounts, for older users that prioritizes a simpler app experience with features like ride updates for family members, saved destinations, and the ability to use a family member’s card for payments. Uber said Senior Accounts present a simpler app experience with larger text and icons, as well as less complex screens. Users can switch this mode on using the accessibility settings in the app. Users in the U.S. can now add older adults to their family account via the “Family” menu under the Accounts tab. Users who manage the family account can add their own payment methods, edit the list of saved destinations, book a ride for older adults, and contact drivers during a ride. People in the family group can also follow senior users’ rides. Uber said senior users can add their Medicare Flex card to pay for eligible medical visits. The company said it plans to make Senior Accounts available worldwide, though it didn’t specify when the feature would roll out to other countries. Uber added teen accounts in a few cities in the U.S. in 2023 and later rolled it out to more regions and countries.
Pagos launches first MCP server to allows LLMs and AI-powered tools to securely query real-time BIN-level card data directly from card networks
Pagos, an all-in-one provider of payments optimization solutions, today announces the launch of its first Model Context Protocol (MCP) Server, making it easier than ever for AI agents and applications to query the payments intelligence available only through Pagos. This MCP Server, designed for their direct-to-network BIN data solution, allows large language models (LLMs) and AI-powered tools to securely query real-time BIN-level card data directly from card networks. Developers and businesses can now plug this data directly into their AI workflows, making it easier than ever to: Get to know your customer base with card details like issuer, card brand, and country data; Design routing strategies around preferable approval rates and processing costs; Finetune your retry strategy; Create BIN-based fraud rules to identify and block issuing banks or specific BINs frequently associated with fraud or carding attacks; Reduce your interchange costs by identifying when a customer’s card qualifies for Level II or III data; Prototype AI tools without building a custom connector to Pagos.