Thomas Mazzaferro, chief AI data and analytics officer at Truist Bank, said the bank partners with providers that use AI for threat detection and to scan the environment to take down attacks. Mazzaferro said his bank uses AI not only for detection but also to scan the entire ecosystem, both on-premise and in the cloud, to map where critical data resides and understand exposure. Truist uses machine learning models for scanning in cases where it has “defined inputs, defined logic, and defined outputs,” he said. For detecting undefined threats and attack vectors, where patterns may differ from normal, the bank uses solutions based on generative AI, which is more tolerant to unstructured data. Models that Truist trains internally on the bank’s own data are less valuable than models trained by vendors on data from multiple banks, Mazzaferro said. He indicated a preference for partnering with vendors and focusing on integrating these solutions and automating the response to alerts and triggers because combining data provides more threat patterns for the models to recognize. He said the focus should be on minimizing bias and ensuring models perform as expected. This happens when a bank establishes guardrails and monitors model outputs in near real time to ensure they remain within defined thresholds. Truist maintains a “champion-challenger” mindset, training a discovery model in parallel with production models so that if a deployed model performs inappropriately, there is an alternative to assess. Mazzaferro noted that while the technology exists, the bigger challenge is overcoming the “human behavioral piece” and resistance to changing how teams think about their work.
Wells Fargo plans to expand further in credit cards and investment banking, while also investing in wealth and commercial banking; it will not expand in mortgages
Wells Fargo CEO Charlie Scharf knows he has a reputation for sternness, but he said that when the bank was finally freed of a $1.95 trillion asset cap by regulators on Tuesday, he became emotional. “Everyone thinks that I’m this tough, tough person … but it’s been so long in the making, it’s impacted so many people so negatively,” Scharf said. “All of a sudden, it’s like it’s all been worth it and everyone’s feeling it.” Scharf took the helm at Wells Fargo in 2019, vowing to repair its deeply entrenched problems from a fake-accounts scandal that erupted in 2016. The bank faced a public outcry, was blasted by lawmakers and slapped with billions of dollars in fines. The Federal Reserve’s decision to lift one of Wells Fargo’s last major punishments this week has largely closed that chapter in its history. It also cements Scharf’s legacy after a grueling turnaround in which he overhauled management, slashed headcount and shed businesses. He is turning his focus to growth after serving almost six years as Wells Fargo’s fixer-in-chief. He plans to expand further in credit cards and investment banking, while also investing in wealth and commercial banking. It will not expand in mortgages, he said. The bank exited many of those operations after they were beset by scandal. As Wells Fargo aims to increase earnings, it plans to raise its dividend to keep payouts consistent for investors, Scharf said. Share buybacks will continue, but their pace will probably slow as the bank invests in growth, he said. Wells Fargo shares were up 0.5% on Wednesday afternoon, having climbed more than 8% so far this year as investors became more optimistic about the bank shedding its regulatory baggage.”I would expect that across all the remaining businesses that we have, with the slight exception of our mortgage business, all have opportunities to grow and produce higher returns. So it’s true of the wealth business through commercial still true of CIB (corporate and investment banking), because even though we’re seeing results and significant upside there, it’s true in our business, and super importantly, it’s true in our consumer and small business banking business, where they were most impacted by the sales practice scandal. We’re just introducing disciplines back to be able to serve customers more broadly and grow in ways that we haven’t been able to.” In some ways, it’s a totally different company. The culture is different here, it’s not a “me” culture. People want to be treated fairly, they want to be paid fairly, but they come here because they want to work together. That is incredibly important. Carried to an extreme, it hurt us because we didn’t make difficult decisions about people, we didn’t confront things. But I do think a culture like that, in a balanced way, is incredible to have. It takes a long time to build.
Square’s conversational AI assistant can answer sellers’ questions about how to use its business technology platform and about trends in their own business by searching its knowledge base and using the seller’s relevant data within its platform
Square has launched a conversational AI assistant that can answer sellers’ questions about how to use Square’s business technology platform and about trends in their own business. The AI assistant, Square AI, is available now in public beta for all sellers in the U.S. and is integrated into the Square Dashboard. “Our goal is to give each seller their own virtual employee that knows every bit of their business,” Willem Avé, global head of product at Square, said. When asked questions about using the platform, the AI assistant searches its knowledge base and provides step-by-step instructions. To answer questions about the seller’s business, Square AI uses the seller’s relevant data within Square to provide the answer. It can answer questions about sales, customers, staff and transactions, enabling sellers to optimize staff hours, identify slow-moving inventory, maximize top sellers and recognize top customers. The company will expand these capabilities throughout the year. To protect the data within the business, the AI assistant is only available for account owners and administrators. In addition, Square never sends sensitive information to model providers or partners, and it ensures no data processed by third-party companies is retained outside of Square systems or used for any type of training
PayPal taps Mastercard’s One Credential feature to enable consumers to set preference whether to pay with debit, installments, prepaid or credit for online or in-store purchases depending on the transaction
Mastercard and PayPal have partnered to co-develop features using Mastercard’s One Credential, a solution that enables consumers to use a single credential when shopping online or in-store. The companies aim to use this solution to give consumers more choice and control over how they pay at checkout, allowing them to access multiple payment options. One Credential can also help PayPal users improve their creditworthiness and progress from debit to installments and other structured credit. “We both want to reduce friction for consumers and bring them more power over how they pay,” Chris Sweetland, senior vice president of partnerships at PayPal, said. Bunita Sawhney, chief consumer product officer at Mastercard, said that the partnership with PayPal will build on “our collective strength of global payments innovation. With One Credential, we’re delivering the personalized digital experiences that build consumer confidence and trust.” Mastercard’s One Credential will allow consumers to choose to pay with debit, installments, prepaid or credit. Users can set their preferences online or in an app. They can also set preferences based on transaction type and time. For example, users can specify their checking account for expenses under $100, their credit card for expenses over $100 and installments for occasional larger purchases. Mastercard is now rolling out One Credential as a network-level capability worldwide.
Phonely’s conversational AI agents reduce response times by more than 70% the awkward delays that immediately signal to callers they’re talking to a machine
A three-way partnership between AI phone support company Phonely, inference optimization platform Maitai, and chip maker Groq has achieved a breakthrough that addresses one of conversational AI’s most persistent problems: the awkward delays that immediately signal to callers they’re talking to a machine. The collaboration has enabled Phonely to reduce response times by more than 70% while simultaneously boosting accuracy from 81.5% to 99.2% across four model iterations, surpassing GPT-4o’s 94.7% benchmark by 4.5 percentage points. The improvements stem from Groq’s new capability to instantly switch between multiple specialized AI models without added latency, orchestrated through Maitai’s optimization platform. The system works by collecting performance data from every interaction, identifying weak points, and iteratively improving the models without customer intervention. “Since Maitai sits in the middle of the inference flow, we collect strong signals identifying where models underperform,” Matai founder Christian DalSanto explained. “These ‘soft spots’ are clustered, labeled, and incrementally fine-tuned to address specific weaknesses without causing regressions.” The performance gains translate directly to business outcomes. “One of our biggest customers saw a 32% increase in qualified leads as compared to a previous version using previous state-of-the-art models,” Will Bodewes, Phonely’s founder and CEO noted. For call centers and customer service operations, the implications could be transformative: one of Phonely’s customers is replacing 350 human agents this month alone.
Fintech OneBanx’s APIs enable banks to integrate cash deposit and withdrawal capabilities into their mobile banking apps via OneBanx kiosks
UK-based fintech OneBanx is integrating cash deposit and withdrawal capabilities into partner banks’ mobile apps, aiming to bridge the gap between digital banking and physical cash access. The company is developing secure APIs to enable customers to initiate and complete cash deposits and withdrawals from OneBanx kiosks using their existing mobile banking apps. This integration complements existing digital payment solutions, providing a more comprehensive service offering. OneBanx’s joint white paper with Enryo highlights the importance of a long-term strategic approach for cash users. Benefits for Banks and Their Customers : Enhanced Customer Experience: Customers can enjoy a unified banking experience, managing their finances and accessing cash through a single, familiar platform. Increased Digital Engagement: Introducing cash access features within bank apps can serve as a gateway for customers who are less digitally active, encouraging gradual adoption of digital banking services. Cost-Effective Infrastructure: Banks can extend their service reach without the overhead of maintaining traditional branch networks, leveraging OneBanx’s kiosk infrastructure.
CSI partners digital engagement provider WaveCX to enable banks to deliver tailored marketing, tutorials and educational experiences based on user behavior directly within their banking apps
WaveCX, provider of personalized, digital product engagement solutions for financial institutions, announced a strategic partnership with CSI, provider of end-to-end financial software and technology. Through this integration, CSI clients using the NuPoint® and Meridian® core platforms are equipped to increase digital adoption and deliver more dynamic customer experiences directly within their banking applications. The partnership opens new possibilities for customer engagement within digital banking environments, allowing financial institutions to go beyond traditional marketing channels. With WaveCX, CSI clients can now: Deliver tailored in-app marketing and educational experiences based on user behavior; Promote awareness and adoption of underutilized digital features; Proactively guide users with contextual messages, tutorials and announcements at the point of need. Jon Tvrdik, CEO of WaveCX “By reaching users directly inside the app, banks and credit unions can increase adoption, improve education, and ultimately drive stronger engagement and loyalty.”
Trust3 AI’s customizable guardrails, integrate with Snowflake RBAC mitigating prompt injection, unauthorized access, and sensitive data exposure
Trust3 AI has unveiled its innovative AI trust layer, focused on improving Cortex AI adoption and providing enterprises with robust tools to address challenges in scaling and managing AI systems. Available as a native app on Snowflake, Trust3 AI key components include—Trust3 IQ, Trust3 Visibility, and Trust3 Guard. Together, these features create a groundbreaking platform that simplifies semantic layer building, enhances contextual understanding, and ensures AI systems’ reliable and secure operation at scale. Trust3 IQ unifies structured and unstructured datasets, delivering a unified semantic layer that bolsters accuracy and enhances retrieval-augmented generation (RAG), and Cortex agents. Offering a significant increase in reliability of conversational AI, Trust3 IQ accelerates AI adoption across multiple industries. Through Trust3 Visibility, enterprises gain real-time observability for all AI assets built on Snowflake and other platforms, enabling teams to measure, catalog, and govern systems effectively. This governance layer provides critical oversight for system behavior, ownership, and performance, mitigating risks related to security, legal and operational efficiency. Additionally, Trust3 Guard powers dynamic, context-aware security controls to safeguard structured and unstructured data. Its customizable guardrails, integrated with Snowflake RBAC and guardrails, mitigate risks such as prompt injection, unauthorized access, and sensitive data exposure, ensuring operational trust and compliance. Trust3 AI accelerates AI adoption and builds trust with end users by: Building enterprise context faster with intelligent metadata and semantic models; Delivering real-time observability for proactive risk mitigation; and Enhancing operational efficiency and reducing AI costs with adaptive controls.
Imandra Universe, a new platform enhances AI assistants like ChatGPT, Claude, and Cursor with advanced logical reasoning capabilities to perform complex reasoning tasks more accurately
Imandra Inc. has launched the Imandra Universe, a new platform that enhances AI assistants like ChatGPT, Claude, and Cursor with advanced logical reasoning capabilities. This platform allows these AI systems to perform complex reasoning tasks more accurately by using Imandra’s symbolic logical reasoning engines. With a quick 10-second setup and an Imandra API key, users can enable their AI to employ this new functionality. The Imandra Universe offers a feature known as Reasoning as a Service®, which integrates into AI systems, allowing them to think more precisely and validate their outputs mathematically. This improvement aims to enhance workflows by enabling AI to delegate challenging tasks effectively to specialized reasoning engines. For example, if Claude is given the job of planning a multi-step event, it often misses important details. However, by utilizing the Imandra Universe, it can delegate the complex aspects of this task, improving its overall performance. In addition to enhancing existing AI assistants, the Imandra Universe positions itself as a tool that could revolutionize how users interact with artificial intelligence, bridging the gap between simple user commands and complex logical tasks. The technology aims to provide real-time support for neuro-symbolic AI, enabling more sophisticated and accurate outputs.
Future AirPods could get lasers to read the wearer’s lips & process requests
Apple is researching how AirPods could use sensors like the ones used in Face ID to read the user’s lips and process what the user wants, even if there isn’t a spoken request. The “Wearable skin vibration or silent skin gesture detector” patent proposes using what it calls self-mixing interferometry to recognize more nuanced gestures. Beyond full head movements like a nod or shake, much smaller ones such as a smile, or a whispered command, could be detected. Deformations in the skin, or skin and muscle vibrations, could be spotted and interpreted by the interferometry sensor. The idea is that as a user speaks, the movement of the jaw and cheeks is detectable through the use of a Vertical Cavity Surface Emitting Laser (VCSEL) in the frame of the device. The idea is that the VCSEL emitter and sensor, similar to the combo used in Face ID, could be in the frame of the device. And, users could select how the AirPods react to different skin and lip movements picked up by that combination of emitter and sensor. In the case of AirPods that go inside the ear, instead of solely over the ear AirPods Max, Apple also says that “the self-mixing interferometry sensor may direct the beam of light toward a location in an ear of the user.” When that light and its reflection back to the sensor alters, it will be because of head or skin and muscle movement. The patent is then specifically about methods by which such movement could be detected, but beyond the specifics, there are two clear benefits. One is that movement detection allows for what Apple calls silent commands. Currently AirPods Pro support a silence nod or shake of the head to accept or reject phone calls, but they could be set to interpret a mouth movement as meaning “skip track.”