AtData, an innovator in email address intelligence, data security, and digital trust solutions, introduced Validation 2.0, a next generation framework redefining email validation. AtData’s next generation email validation leverages its behavioral activity network to provide ongoing, real-time, intelligence-driven verification. This enables marketers to confirm an email is legitimate and understand its real-world activity, engagement likelihood, and potential risk. Brian Burke, AtData’s VP of Product “By integrating our exclusive scoring, monitoring and trust functionality, we’re empowering marketers with real-time, predictive insights so they can prioritize engaged consumers, suppress inactive or risky addresses, and cut through the inbox clutter with more confidence.” Powered by AtData’s proprietary scoring, monitoring, and detection infrastructure, Validation 2.0 delivers continuous visibility into email address health, value, and risk. This includes signals indicating behavioral engagement, identity changes, and threat indicators such as disposable or bot-generated addresses. AtData’s always-on framework supports better customer segmentation from the moment of email collection helping improve engagement and increasing ROI. With inboxes more competitive, data decay accelerating, and promotion abuse rising, organizations need advanced email verification. Combining AtData’s deep identity expertise, advanced machine learning, and decades of historical email intelligence gives marketers the full picture, allowing them to send smarter and act faster to build trust.
Workato’a AI app helps employees search across every system and data source, receive personalized intelligent assistance with full enterprise context, take secure, role-based multi-step actions and launch workflows from a single interface
Workato has launched Workato GO, an AI super app designed to help employees search, act, and orchestrate work across all systems, apps, and data sources. Workato GO connects to all business tools, providing a single starting point for intelligent, secure, and scalable work. It combines three essential capabilities into a single experience: searching across every system and data source, receiving intelligent assistance tailored to each user, and taking secure, role-based actions. Workato GO is built on Workato ONE, the leading enterprise platform that powers integration, automation, and trusted agent execution. It enables users to complete workflows, kick off processes, and orchestrate results directly from a single interface. With GO, customers will have access to: Enterprise Search: Search across all your systems, data, and workflows. A single place to search across all your applications, documents, and processes, so employees can find exactly what they need, fast. Enables employees to instantly find information across all of their company’s documents, data, applications, and business processes from a single, unified interface. Employee Assistant: The personalized starting point for every employee. Combines intelligent assistance with full enterprise context, and the ability to take action without switching between tools. Deep Action™: Move from knowledge to execution. Take multi-step actions across multiple systems, trigger automations, and launch workflows—including human-in-the-loop processes—right from the search results or assistant. Agents at the Core: Flexible, open agent architecture that integrates Workato and third-party agents, enabling automation and orchestration across all systems. Extensibility: Easily extend and customize capabilities with recipes and agents—adapting Workato GO to your unique business needs.
TELUS Digital’s off-the-shelf STEM datasets including coding and reasoning data are curated by diverse pool of experts to offer enterprises access to high-quality, AI-ready data that has been cleaned, labeled and formatted
A new TELUS Digital survey of 1,000 U.S. adults found that 87% respondents (up from 75% in 2023) believe companies should be transparent about how they source data for GenAI models. Additionally, 65% believe that the exclusion of high-quality, verified content, such as information from trusted media sources (e.g. New York Times, Reuters, Bloomberg), can lead to inaccurate and/or biased large language model (LLM) responses. “As AI systems become more specialized and embedded in high-stakes use cases, the quality of the datasets used to optimize outputs is emerging as a key differentiator for enterprises between average performance and having the potential to drive real-world impacts,” said Amith Nair, Global VP and General Manager, Data & AI Solutions, TELUS Digital. “We’re well past the era where general crowdsourced or internet data can meet today’s enterprises’ more complex and specialized use cases. This is reflected in the shift in our clients’ requests from ‘wisdom of the crowd’ datasets to ‘wisdom of the experts’. Experts and industry professionals are helping curate such datasets to ensure they are technically sound, contextually relevant and responsibly built. In high-stakes domains like healthcare or finance, even a single mislabelled data point can distort model behavior in ways that are difficult to detect and costly to correct.“ In response to evolving industry dynamics, TELUS Digital Experience has launched 13 off-the-shelf STEM (science, technology, engineering and mathematics) datasets, including coding and reasoning data that is critical for LLM advancements. The datasets have been expertly-curated by a diverse pool of contributors, including Ph.D. researchers, professors, graduate students and working professionals from around the world. This gives enterprises access to high-quality data that has been cleaned, labeled and formatted for immediate integration into AI training workflows.
DataKrypto and Tumeryk’s solution combines real-time encryption of RAG data, model weights and prompt payloads with self-calibrating prompt security to provide end-to-end protection across all stages of generative AI workflows
AI trust scoring company Tumeryk Inc. announced a strategic integration with AI encryption firm DataKrypto Co. to launch a joint service that they claim offers the world’s first encrypted guardrails for operational AI security. The new Encrypted Guardrails for Operational Security combines DataKrypto’s real-time encryption of retrieval-augmented generation data, model weights and prompt payloads with Tumeryk’s AI Trust Score, self-calibrating prompt security and responsible AI controls to provide end-to-end protection across the entire AI pipeline. The integrated solution encrypts all stages of generative AI workflows, from data retrieval through model inference and response generation, while simultaneously enforcing compliance and policy alignment. The two companies argue that while traditional AI guardrails focus on monitoring model outputs, they often leave critical data flows vulnerable to attack or misuse. The integration between Tumeryk and DataKrypto closes the gap by encrypting every component of the AI pipeline, from vector embeddings and foundation models to tool-calling prompts and guardrail policies. The result is end-to-end protection that strengthens the AI attack surface while also preventing threats such as data exfiltration, prompt injection and model manipulation. Core to the new solution is DataKrypto’s FHEnom technology, which allows encrypted computation on embeddings and model weights while maintaining hardware-enforced isolation within secure enclaves. Tumeryk complements this with real-time prompt inspection, using self-calibrating guardrails to detect and block noncompliant or potentially harmful inputs before they reach the model.
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.
Mitiga cloud incident response company helps security operations teams with triage, augmented investigation and accelerated threat remediation across multicloud environments
Cloud incident response company Mitiga Security launched Helios AI, an AI-powered security operations center assistant that helps security operations teams with triage, augmented investigation and accelerated threat remediation across multicloud environments. Helios AI is designed specifically for modern, dynamic cloud environments to deliver vastly improved operational efficiency. The service optimizes security team resources and eliminates tedious manual workflows to deliver what Mitiga claims is the fastest mean time to detect and mean time to respond available. The platform helps SecOps teams reclaim critical time, reduce risk exposure and improve threat detection and incident response across cloud and software-as-a-service environments by significantly reducing alert noise and surfacing only actionable insights. The first Helios AI feature available to customers is AI Insights, an automated SOC assistant that cuts through alert noise to deliver 90% faster triage and 70 times faster alert close rates. Early simulations run by Mitiga are said to show how Helios AI and AI Insights have significantly outperformed traditional alert systems in both accuracy and speed. The aim is to provide a strategic view for cloud security leaders and how they can use Helios AI and AI Insights to prepare their teams and environments for what’s next.
Incogni study finds popular AI models are collecting sensitive data such as email addresses, phone numbers, photos, precise location and app interaction data and sharing it with unknown third parties
Findings from Incogni study reveal that some of the most popular, from companies like Meta, Google, and Microsoft, are collecting sensitive data and sharing it with unknown third parties, leaving users with limited transparency and virtually no control over how their information is stored, used, and shared. Key findings: Meta.ai and Gemini collect precise location data and physical addresses of their users; Claude shares email addresses, phone numbers, and app interaction data with third parties, according to its Google Play Store listing; Grok (xAI) may share photos provided by users and app interactions with third parties; Meta.ai shares names, email addresses, and phone numbers with external entities, including research partners and corporate group members; Microsoft’s privacy policy implies that user prompts may be shared with third parties involved in online advertising or using Microsoft’s ad tech; Gemini, DeepSeek, Pi.ai and Meta.ai, most likely are not giving users the ability to opt out of training the models with their prompts; ChatGPT turned out to be the most transparent when it comes to the information on what prompts will be used for model training, and a clear privacy policy.
J.P. Morgan’s new Active High Yield ETF will devote at least 80% of its portfolio to junk-rated bonds
Finite opportunities in private credit are creating public, high-yield debt opportunities, J.P. Morgan Asset Management CEO George Gatch said. Gatch made the comment as J.P. Morgan unveiled its J.P. Morgan Active High Yield ETF. The fund will devote at least 80% of its portfolio to junk-rated bonds and opened with a $2 billion anchor investment. While junk bond spreads to Treasuries are “tight,” yields are attractive compared to equities, and default rates in this space are low, the report said. Beyond that, alternatives to high-yield debt like private credit are being overrun with investors. With that in mind, the liquidity advantages and high yields of publicly traded bonds provide a good entry point. “There’s a lot of money and investors chasing finite opportunities in the private credit market,” Gatch said, per the report. “You also have liquidity tradeoffs. You take those two things in combination and on a marginal basis, I would put my marginal dollar in public high-yield rather than private credit.” The private credit space is a key part of the capital spectrum for firms that cannot access, or choose not to get, normal bank channels.
FedNow hikes transaction limit increase from $500,000 to $1 million to support higher-value use cases; also enables defining dollar value and transaction velocity thresholds based on customer segments
A new account activity threshold feature is now available for the FedNow Service, allowing financial institutions to strengthen risk mitigation efforts by defining dollar value and transaction velocity thresholds based on customer segments. The new functionality coincides with a transaction limit increase from $500,000 to $1 million to support higher-value use cases, including business-related transactions. “These new value-added features offer FedNow participants more options to customize their instant payments profile, adding to the suite of available tools that allow financial institutions to tailor activity according to risk management needs and customer activity,” said Mark Gould, chief payments executive for Federal Reserve Financial Services. “Feedback from the industry has been invaluable, and we intend to remain agile and responsive to new and changing customer needs as instant payments grow and mature.” Account activity thresholds provide further control as more financial institutions enable “send” capabilities on the network. Financial institutions can set parameters around sending activity for a wide range of customer segments, from established business customers to new individual account holders, as an additional level of security. “With these controls, our customer base of community banks will have more confidence in expanding their instant payment capabilities, especially when it comes to ‘send’ functionality, which will ultimately help all financial institutions remain competitive in the marketplace,” said Brooke Tiedt, senior vice president, payments and cash management at Bankers’ Bank. “The ability to add controls based on specific customers helps set the FedNow Service apart from other payment offerings.” The FedNow Service is nearing its second anniversary with approximately 1,400 banks and credit unions on the network across all 50 states. Community banks and credit unions make up more than 95% of total participants.
Block claims to have prevented $2 billion in potential P2P fraud scams since 2020, aided by real time in-app Cash App payments warnings to examine their transactions before moving ahead
Block Risk Lead Brian Boates found that even tech-savvy young consumers who use their phones as a conduit to everyday life reported the challenges of avoiding scams. “The last time we went into the field, we found that about 3 in 10 consumers say they’ve been scammed, and about 40% of Gen Z” has fallen prey to the fraudsters, Webster said. This statistic underscores a challenge for the payments industry. It must protect individuals who value and use peer-to-peer (P2P) payments as a staple of their daily financial lives. To that end, Block announced Thursday (June 26) the prevention of approximately $2 billion in potential P2P fraud scams since 2020, aided by advanced technologies and the in-app Cash App payments warnings feature that alerts customers in real time to examine their transactions before moving ahead. A challenge in combating scams lies in the nature of the transactions themselves. Many of them are authorized transactions. Unlike traditional fraud where an unauthorized party gains access to an account, in scam scenarios, “the customer is willing and wants to proceed with the payment,” Boates said. This makes intervention particularly complex, as it requires interrupting a user’s determined intent. The emotional conviction tied to these transactions often supersedes rational caution. Beyond direct scams, the payment industry also grapples with the persistent issue of first-party fraud. This occurs when an individual misrepresents a legitimate transaction as a scam to reclaim funds. Block’s various lines of defense against these evolving threats are rooted in its technological prowess. “Block is a technology company,” Boates said. “We take a very technology-forward approach to solving these kinds of problems.” He said that “when it comes to fraud and scam detection, it’s really rooted in machine learning. We’ve built a number of models internally using all of the data points that we have historically that have gotten really, really good at detecting potentially scam payments in real time.” Machine learning powers the warning feature where the company intervenes with users when the models signal a transaction may be high risk, rather than introducing friction into each payment, he said. The warning “gives customers a moment to pause, reflect and reconsider [the transaction], if it feels right, and if they’d like to proceed with the payment or not,” Boates said. The precision of these warnings is a key factor in their effectiveness. They are issued for only about 1.5% of P2P payments made through Cash App, he said. Beyond these warnings, Block’s models can take more definitive action when risk levels spike.