TD Bank Group plans to invest $1 billion over a two-year period to beef up its anti-money-laundering controls, after compliance failures led to historic regulatory penalties and handcuffed its U.S. growth. The bank also juggles a new restructuring plan, the scaling back of its American business and growing economic uncertainty due to U.S.tariff policies. The company had previously projected spending $500 million on anti-money-laundering remediation efforts during the fiscal year that ends in October, as it upgrades its training, analysis capabilities and protocols. TD Chief Financial Officer Kelvin Tran told analysts that the bank expects similar investments in the fiscal year that ends in October 2026. “We wanted to give the Street a sense of what 2026 was going to look like,” Salom said. “The composition of spend might change a little bit. It might be a little less remediation, more validation work, more lookbacks, monitor costs, et cetera. … But we think the overall spend level is going to be similar.” Across the first two quarters of 2025, the bank has invested $196 million on the anti-money-laundering compliance efforts. Salom said there will be an uptick in those expenses in the back half of the year as the company delves “into the meat of our remediation delivery programs.” TD plans to deploy machine learning technology in the third quarter to “increase investigative productivity,” along with additional reporting and controls for cash management activities. The bank feels confident about its expense guidance for 2025 and 2026, and those costs will eventually decline “at some point in the future,” Salom said. TD also said that it’s on track to meet its previous projection of a 10% reduction in U.S. assets by the end of October. At the end of April, the U.S. bank had about $399 billion of assets, putting it below the $434 billion cap imposed by the Office of the Comptroller of the Currency. The bank sold or ran off about $11 billion in U.S. loans during the second quarter, and announced plans to wind down a $3 billion point-of-sale financing business that services third party retailers in the U.S. TD also plowed ahead with plans to remix its bond portfolio by selling relatively low-yielding bonds to reinvest in higher-returning securities. Salom said the bank should meet its forecast of restructuring $50 billion of securities in the next few weeks. The bank expects to generate a benefit to net interest income of close to $500 million between November 2024 and October 2025, he said. “We think new CEO Raymond Chun is putting the bank on the right track,” wrote Maoyuan Chen, an equity analyst at Morningstar, in a note. “2025 will be a transitional year as TD is actively remediating its US anti-money-laundering system with elevated expenses and repositioning its US balance sheet for its asset cap growth limitations.”
JPMorganChase democratized employee access to gen AI but per-seat licensing costs model is a roadblock
JPMorganChase was the first big bank to roll out generative AI to almost all of its employees through a portal called LLM Suite. As of mid-May, it’s being used by 200,000 people. “We think that AI has the potential to really deliver amazing scale and efficiency as well as client benefit,” Teresa Heitsenrether, chief data and analytics officer, told. The bank, like many others, has used traditional AI and machine learning for years in areas like fraud detection, risk management and marketing. “But the big surprise really came with generative AI, which really opens up new possibilities for us,” Heitsenrether said. LLM Suite is an abstraction layer through which large language models like OpenAI’s GPT-4 are swapped in and out. The models are trained on proprietary JPMorganChase data. The bank’s lawyers use LLM Suite to analyze contracts. Bankers use it to prepare presentations for clients and to generate draft emails and reports. The project is “advanced in scope and ambition,” said Alex Jimenez, lead principal strategy consultant at Backbase. “Deploying a proprietary large language model at this scale is an industry-leading move. Unlike others, they aren’t just testing but embedding it deep into the daily workflows of bankers, compliance teams, technologists. The real advancement isn’t just the tech but the institutional integration.” This project is setting the tone for other banks, he said. “The rollout likely puts pressure on peer banks to accelerate or scale up their own gen AI initiatives. It is influencing vendor roadmaps and internal AI governance discussions across the industry.” The bank tests and vets new models for safety and security, as well as their applicability to different use cases, before bringing them into its LLM Suite. Some large language models are good at synthesis and reasoning, while others are good at coding or complex document analysis, Waldron said. Small models can be fine-tuned for specific tasks. Generative AI models generally have per-seat licensing costs, which can add up for a bank the size of JPMorganChase. “That’s been one of the roadblocks to widespread adoption, because business leaders naturally are asking the question up front, what’s the ROI for that particular person?” Waldron said. But because JPMorganChase built an internal platform, the only variable cost is compute, he said. If an employee doesn’t use it, the bank does not pay for it. “That value proposition turned out to be very desirable to business leaders,” Waldron said. For its overall AI adoption and use of AI, JPMorganChase has been at the top of Evident’s AI Index from the scorecard’s launch in 2023.Real-time, accurate data is important for these models to generate useful answers. The bank is gradually connecting its datasets to LLM Suite, including all of its news subscriptions and earnings transcript libraries. “When these get connected and distributed to the whole population, all of a sudden, employees can do things in an automated way that they could never do before,” Waldron said. (The bank will still pay for its news subscriptions, but for firmwide access rather than individual accounts.)
BOK Financial creates a content site offering timely articles and videos on economic and personal finance contributing to higher levels of “earned media” — exposure gained through social media sharing and other channels
Bankers are often reporters’ go-to sources for economic and personal finance coverage. BOK Financial’s CMO Sue Hermann thought the bank could get some direct benefit from that. The possibilities that can be realized when a bank decides to deploy its experts to produce “brand journalism” excited Sue Hermann, CMO at BOK Financial, parent of Bank of Oklahoma. Not only can brand journalism deliver meaningful content to customers and potential customers, rather than the usual pabulum, she says, but it can begin to improve the flagging degree of trust that studies still show the industry suffers from. Today, BOK Financial produces “The Statement,” a content site offering timely articles and videos. The site features four sub-channels — “Your Money,” “Your Business,” “Perspectives” and “Community.” Since 2019 the bank’s team of internal experts and writers, as well as freelance writers, produce approximately 150 articles or videos annually. Hermann says the critical difference is “creating a need, rather than selling a thing. Not talking about checking accounts, but helping people understand the importance of long-term planning for their financial needs.” Brand journalism “is a long-term play and it takes a long time for some people to get on board,” says Megan Ryan, the bank’s director of content strategy. This not only includes superiors who want proof that the technique produces results, but even experts within the bank. She and Hermann say that often the best people on a given subject area start out feeling that they’re just bankers, and not media material. But the bank has tracked reader and viewer behavior in multiple ways and Hermann says the content team is garnering results. The bank tracks return users and Hermann says people come back for more articles and videos. (The bank filters bots and employees out of its figures.) In addition, The Statement contributes to higher levels of “earned media” — exposure gained through social media sharing and other channels. Building exposure for the bank in this way, rather than pouring on email after email and then sending those who click through to a page about checking (yes, this is a bugaboo for Hermann), she says. “There is huge value in delivering information in a way that isn’t salesy, because that aligns with our brand and developing long-term relationships — doing what’s best for the client,” says Hermann. Hermann says the bank learned early on that making a success out of this technique takes dedication and regularity. Another helpful element is cross-pollination. Something setting BOK Financial apart from some other large banks is that both marketing and corporate communications report to Hermann as CMO. In the early days, the two functions tended not to leave their swim lanes, as Hermann calls the divide, but now more sharing of ideas and information regarding The Statement occurs. Meetings with line-of-business staff sometimes prompt marketing staff to ask what questions the bankers are hearing from their customers. This may pinpoint an issue and then the right approach to address it has to be settled. The idea is not just to chime along with other media, but to add a viewpoint of bank experts or a round-up informed by that expertise. Hermann and Ryan says its helpful to have professional journalists on the staff or as regular freelancers, because they are not only comfortable with the need to crank out articles on a timely basis, but also the ability to drop.
Capital One Auto Refinance division uses ‘Swiss cheese’ approach to fraud prevention – a combination of risk prevention software and alternative data used to verify transactions
Capital One is using a “Swiss cheese” approach, for which a combination of risk prevention software and alternative data is used to verify transactions, Head of Auto Refinance Allison Qin said. “You have to have a multilayered approach. One slice might have a hole in it, but if you have 20 slices stacked up, you’re less likely to make it through the stack of cheese.” — Allison Qin, Capital One. The lender uses Capital One credit card transaction history and biometric data in its proprietary fraud prevention models, Qin said. Auto lenders’ total estimated loss exposure from fraud reached $9.2 billion in 2024, a 16.5% year-over-year rise, according to risk management platform Point Predictive’s March 25 report. “Fraud is continuously evolving and getting harder to spot, so it’s imperative that dealers and lenders work together to solve [industry fraud],” Qin said. Like lenders, dealerships are implementing multiple fraud prevention systems. Morgan Automotive Group, with more than 75 retail locations in the state, uses an “eyes wide open” approach in which dealers are vigilant about identifying scams, Justin Buzzell, finance vice president of the group, said. For Morgan Automotive Group, those protections include: A red flags check, which looks at customer identification;
A Department of Highway Safety and Motor Vehicles check; A synthetic fraud check, which looks for mixes of real and fake information; A biometric scan; and Video records of all interactions with customers to show “we’ve done everything we could.” “If you pass all of that, we’ll sell you a car,” Buzzell said. Dealerships and lenders agree that notifying each other about fraudulent encounters helps the industry; however, there’s no easy place to do that yet, West American Loan Chief Executive and President Sean Murphy said. If a centralized portal, similar to e-contracting platform RouteOne, allowed dealers and lenders to share potential fraud signs, industry players could work together to stop scams, Murphy said.
Amazon is testing short-form audio product summaries on product detail pages, featuring AI-powered experts discussing key features
Amazon is testing short-form audio product summaries on product detail pages, featuring AI-powered experts discussing key features. The feature makes product research fun and convenient, making shopping easier for customers. Customers can listen to the summaries by tapping the “Hear the highlights” button in the Amazon Shopping app. The feature is currently available to select U.S. customers and will roll out to more customers in the coming months. The feature uses large language models (LLMs) to generate scripts, pulling from Amazon’s product catalog, customer reviews, and information from across the web, and then translating the content into short-form audio clips. AI-powered short-form audio content builds on Amazon’s work to make shopping faster, easier, and more fun. Some of our other AI-powered shopping features that help customers save time and make more informed decisions include:
Rufus, Amazon’s generative AI-powered shopping assistant that can answer questions on a variety of shopping needs and products—it’s like having a shopping assistant with you any time you’re in our store.
Shopping Guides, Amazon’s simplified product research tool that leverages generative AI to bring together dynamic shopping guidance and product recommendations on over 100 product types.
Interests, an AI-powered feature that works on your behalf to continuously monitor new products in Amazon’s store that match your interests and passions.
Review highlights, an AI-powered summary of common themes across reviews that can help you understand product sentiment at a glance.
Buy for Me, a new experiment in beta that allows you to complete purchases from other brand retailer websites if Amazon doesn’t sell the item directly, using agentic AI that doesn’t require human intervention.
NIST releases new AI attack taxonomy with expanded GenAI section and recognizing the extensive use of third-party foundation models in the AI supply chain, and the potential harm of malicious and backdoored models
The National Institute of Standards and Technology (NIST) published a new 2025 version of its adversarial AI taxonomy, first published in January 2024. The latest version of “Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations,” released March 2025, supplies significant updates, including expanded sections on generative AI (GenAI) and key challenges, and a standardized index for more efficient navigation and referencing. “Overall, we updated the content to reflect the progress over the year since the previous version, including terminology, glossary, and bibliography,” Apostol Vassilev, report co-author and research team supervisor at NIST’s Information Technology Laboratory, Computer Security Division, told. The report is designed to be used in conjunction with NIST’s AI Risk Management Framework to help organizations understand how AI models can be misused by attackers and how these attacks can be combatted, Vassilev said. The taxonomy report is divided into separate sections for predictive AI (PredAI) and GenAI, with the GenAI section seeing the most substantial change in the 2025 update. “We renamed the Abuse class of attacks to the Misuse class […] in order to handle a wider range of exploits and align our standard with other NIST and external standards,” Vassilev explained. This change adds model jailbreaks, data poisoning and fine-tuning circumvention under the umbrella of misuse, where an attacker seeks to bypass restrictions and produce potentially harmful AI outputs. The section on supply chain attacks saw significant changes, with distinct subsections on data poisoning and model poisoning attacks. This change recognizes the extensive use of third-party foundation models in the AI supply chain, and the potential harm of malicious and backdoored models.A new section on the security of AI agents noted that these autonomous AI systems can be vulnerable to many of the same exploits as traditional large language models (LLMs), with added risks due to their expanded capabilities. The 2025 report also includes a more detailed description of the GenAI stages of learning to help readers better understand attacks targeting specific learning stages. This information is further incorporated into the guidance on mitigations for direct prompt injection attacks, with interventions divided into pre-training, post-training, evaluation and deployment stages. A longer, updated list of indirect prompt injection techniques was added in the 2025 report; for example, the section highlights self-propagating injections, where a model reads an email that instructs it to send malicious emails to everyone in the user’s contact list. The GenAI section concluded with a new subsection on adversarial machine leaning (AML) benchmarks, referencing nearly a dozen different benchmarking tools and frameworks to help assess models’ susceptibility to varied attacks. The concluding section on key challenges and discussion underwent an overhaul in the latest report, including updated information on supply chain challenges, new subsections on risk management and mitigation evaluations, and a lengthier discussion on tradeoffs between the attributes of trustworthy AI. The new section on evaluation noted a lack of reliable benchmarks to assess the effectiveness of proposed AML mitigations and calls for more research to develop reliable, standardized methods.
Snoop launches Variable Recurring Payments to supercharge automated saving- allowing users to set flexible, automated deposits from their current account into their Snoop savings account on a weekly or monthly basis
Snoop has launched Variable Recurring Payments (VRPs), letting users automate savings with ease and stay on track with financial goals – all powered by Open Banking. Snoop’s new VRP functionality allows users to set flexible, automated deposits from their current account into their Snoop savings account on a weekly or monthly basis – on the day that suits them. This new capability builds on the app’s existing savings features, which already include smart insights and nudges that help customers shift spare cash into high-interest savings. John Natalizia, chief executive officer and co-founder of Snoop said “With VRPs, we’re unlocking a new level of control and ease. This is about building better habits with less effort – and helping people grow their money without needing to think about it every day.” Since launch, the Snoop savings account has gained strong traction. Over 90% of customers fund their accounts using Open Banking, preferring seamless, secure transfers over manual top-ups. The Snoop savings account offers: 4.25% AER / 4.16% gross (variable) interest; Daily interest payments; Easy access: same working day if requested before 11am; Open from just £1, save up to £85,000; FSCS protection up to £85,000 (held with Vanquis Bank Limited). Over 80% of users have set savings goals, most aiming to build an emergency fund. Snoop recommends monthly contributions and nudges users when spare cash is available. This will expand to include advanced sweep rules, roundups, and payday savings, offering even more intelligent automation. Natalizia added “Unlike traditional accounts, Snoop actively helps customers optimise their savings.
BlackRock’s Aladdin integrates Passthrough’s digital onboarding—featuring standardized investor questionnaires, automated data collection, and embedded compliance checks—to streamline private market workflows and enhance investor experience on eFront
Passthrough and Aladdin, BlackRock’s technology business, announced a partnership that integrates Passthrough’s digital subscription technology within the eFront platform to offer a unified investor experience. The collaboration enables common clients – from general partners to asset servicers – to digitize their investor onboarding process and deliver scalable investor relations solutions for their clients. Now live, the integration enables eFront users to streamline and automate onboarding and fund closings for their investors. Using Passthrough’s technology, it’s now easier to distribute and execute subscription documents electronically, accelerating subscription workflow and reporting. Over time, the two companies will collaborate further to embed Passthrough’s full onboarding flow – including subscription agreements, tax forms, and AML requests – within eFront’s investor experience. Through this partnership, BlackRock will also leverage Passthrough’s technology to streamline onboarding for clients in its private markets business. Passthrough automates investor onboarding and compliance workflows for private funds. From subscription documents and tax forms to AML and KYC processes, Passthrough eliminates friction for both investors and fund managers. The platform connects directly to CRMs, investor portals, and fund admin systems to provide a seamless, API-first experience across the investor lifecycle.
Pagaya the provider of AI-driven underwriting technology brings $1 billion in additional POS BNPL funding capacity through securitization
Pagaya Technologies has launched POSH (Pagaya Point of Sale Holdings Trust), a new asset-backed revolving securitization program focused on point-of-sale financing (“POS”), which will enable Pagaya to be a growth catalyst for point-of-sale providers in the U.S. By combining increased funding capacity through POSH with Pagaya’s embedded AI-driven underwriting technology, lenders can approve more customers at the point of sale. This boosts merchant satisfaction, broader adoption and activation. The inaugural transaction, POSH 2025-1, is a $300 million AAA-rated deal, with an 18-month revolving period, and is expected to close next week. The revolving nature of the deal structure allows Pagaya to reinvest capital as loans are repaid, significantly expanding overall lending capacity, while also increasing capital efficiency. The POS product is optimized for loans with shorter durations – typically six months – and credit profiles in the 600+ range, empowering lenders to approve more customers without additional credit risk. As demand continues to surge across the POS ecosystem, Pagaya is delivering new capital solutions to drive the next phase of lending partner growth. Sanjiv Das, Co-Founder and President of Pagaya said “It enables Pagaya to support our existing POS lending partners at scale by powering more customer approvals, which in turn drives greater merchant satisfaction and activation. These results are delivered seamlessly through our API integration into our partners’ origination systems, making it easy to unlock value for both lenders and merchants.
Robinhood proposes RWA tokenization framework and exchange for traditional assets, integrating offchain trade matching with onchain settlement
Robinhood has submitted a proposal to the US Securities and Exchange Commission (SEC) for a federal framework for tokenized real-world assets. The proposal introduces the Real World Asset Exchange (RRE), a blockchain-based trading platform that modernizes securities infrastructure by integrating offchain trade matching with onchain settlement. The proposal aims to simplify compliance for broker-dealers and asset managers across the US and reduce regulatory uncertainty. The RRE will treat tokenized assets as direct representations of their traditional counterparts, allowing regulated brokers to manage these assets within existing compliance systems. The platform will support 24/7 trading of tokenized assets under established regulatory protections, with offchain trade matching for speed and onchain settlement for finality and auditability. The proposal could redefine the U.S. tokenization landscape and pave the way for other financial institutions to enter the market confidently.
