The Department of Housing and Development is seeking information about the impact that the frequent use of Buy Now, Pay Later (BNPL) products may have on borrowers’ ability to meet housing-related expenses, including rent or mortgage payments. Comments are due on or before August 25, 2025. HUD noted that use of BNPL services is growing rapidly and is changing how individuals manage short-term expenses. “BNPL loans essentially create ‘phantom debt’ that mortgage lenders may not be readily able to detect as needed to fully assess a borrower’s outstanding obligations or debt management behavior,” according to HUD. Interestingly, HUD did not expressly address the ramifications of BNPL arrangements with regard to the “ability to repay” requirements applicable to residential mortgage loans. HUD said that FHA’s policies would largely exclude BNPL loans from consideration in underwriting because closed-end debts are not required to be included if they will be paid off within 10 months from the date of closing and the cumulative payments of all such debts are less than or equal to 5% of the borrower’s gross monthly income. The department continued, “Understanding the intersection between BNPL lending and housing-related expenses is crucial for determining whether FHA’s current policies are adequate or if development of BNPL-specific policies are warranted for FHA to continue to support financial self-sufficiency and housing stability.”
RIA industry snapshot displays growth of wealth management in 2024, with AUM crossing $145 trillion
Registered investment advisory firms topped previous records in many key business metrics in 2024, with assets under management crossing $144.6 trillion. The number of firms registered with the Securities and Exchange Commission and their AUM, clients and employees reached new heights from prior records, as shown in the below charts based on the latest yearly “Investment Adviser Industry Snapshot” by the Investment Adviser Association, a trade group, and COMPLY, a compliance firm. The overall figures, though, obscure some challenges posed by the need for organic growth rather than through M&A and asset appreciation. And any financial advisor thinking about joining an RIA or launching a new one must consider factors ranging from the macroeconomic forces affecting the entire industry to the many potential issues that could play out among their clients and employee teams, according to Julie Genjac, the vice president of applied insights for Hartford Funds, where she coaches advisory teams in practice management. “Interestingly, many new entrants into the RIA space are not immediately looking to scale or merge,” she said in an email. “Instead, they’re eager to test their independence, see how their team functions autonomously and gain firsthand experience running their own firm. While some may eventually choose to join a larger RIA for added infrastructure and support, the initial appeal of independence continues to drive a steady stream of new firms into the market. This trend underscores the enduring appeal of autonomy and customization in wealth management and suggests that, despite consolidation headlines, the entrepreneurial spirit within the industry remains strong.” Other trends fueling the RIA movement stem from that flexibility in areas like marketing, client experience and the business model of a firm, and the way that advisors are “increasingly attracted to the opportunity to retain a greater share of revenue while also having the freedom to design compensation models that suit their teams,” Genjac added. As with any study tracking RIAs, the IAA/COMPLY industry snapshot chooses specific criteria that will bring some data noise to any conclusions about the wealth management business. The report covers every type of SEC-registered firm, so the numbers include both wealth and asset management firms and those catering to retail clients and institutions.
Overhaul of rewards for their luxury credit cards by Chase and Amex means smaller issuers must fine-tune their offerings to constantly reevaluate their relationships with their customers, across all segments
When Chase and American Express unveiled plans to enhance rewards for their luxury credit cards—and raise their fees—it seemed that these lenders were focusing on the most rock-solid customer base amid economic upheaval. Though macroeconomic factors have played a part in the renewed focus on affluent customers, these moves involve much more than is apparent at first glance. Brian Riley, Director of Credit Payments at Javelin Strategy & Research, said smaller credit card issuers can take critical cues from the top issuers’ strategies. “The timing of doing this is good because they’ve got to integrate this portfolio, and all of a sudden Chase is going to lose its position as top issuer—it’s now going to be the new Capital One. With all the chaos, the timing is right for Chase and Amex to readjust this piece.” The issuers are recalibrating by addressing the three best segments in the credit card market. First are the big spenders, who can afford to make the substantial investment in a product that others receive for free. Next are the strategic buyers, who are willing to pay a high fee for the potential to reap high rewards. The final segment is responsible cardholders, those who have FICO credit scores above 720. Another attractive trait about the premium segment is that Discover doesn’t have an offering in this space. Capital One does—with its Venture X card—but the$395 annual fee card doesn’t deliver the same caliber of rewards as the Chase and Amex products do. “Capital One and Discover are middle-market players, but they do have some great accounts,” Riley said. “So here the two biggest players on the premium side aim directly at the top-end segment, so that’s a big deal. “There are subsegments within that, because you also have the smaller banks in the mix. Here, you are taking on little community banks; you’re marching into their area. You’re presumably going to be taking the top of all their customers and leaving the middle-market stuff there, so the portfolios become less sound outside of Chase and Amex.” Smaller banks won’t be the only institutions affected as Amex and Chase duke it out over premium cards. Other top issuers, such as Bank of America, Citi, and Wells Fargo, will have to shift to defend their top customers. However, the affluent cardholder base isn’t the only segment that these institutions must safeguard. “Another big thing here is that—for the first time—Chase is adding their small-business card into the mix,” Riley said. “Now, Amex has always done that in the Platinum card, but it shows you how Chase is addressing the market. That is a real big focus, and it’s a great time to be in the market because with small businesses—yes, some will fail—but many will succeed, and it’s a good choice.” Investing in the SME market is a strong strategy because typical card spending ranges from $20,000 to $50,000 per month. The arrival of Chase means other issuers must reevaluate their offerings to this sought-after segment. Because two of the strongest credit card issuers are enhancing their premier reward programs, other issuers should consider following suit. However, this should be done only if the issuer’s business allows for it. Adding 100 basis points to a card might make it more competitive but also makes it less profitable. Another area where smaller institutions can follow in the footsteps of top issuers is by benchmarking their card data. Companies like Chase and Amex are constantly adjusting their products based on market conditions, as evidenced by data from Javelin’s Card Bench, a competitive intelligence card acquisitions tool. In addition to fine-tuning their offerings, issuers should also constantly reevaluate their relationships with their customers, across all segments.
J.P. Morgan analyst is more bullish on Chime’s stock citing the company’s ability to attract, and make money off, people earning up to $100,000 a year
J.P. Morgan analyst Tien-tsin Huang issued a more bullish view on Chime Financial Inc.’s stock than a number of his peers, citing the banking services company’s ability to attract, and make money off, people earning up to $100,000 a year. “Chime cracked the code of scaling financial services as a non-bank by earning the trust of everyday Americans with a ‘low cost, no cost’ banking model that improves the financial lives of those historically burdened by fees and minimum balance requirements,” Huang wrote in a research note. Huang initiated coverage of Chime’s stock with an overweight rating and a $40-per-share price target, implying about 25% upside from current levels. The company has built the largest direct deposit base of any U.S. financial-technology company while ranking sixth as a debit-card issuer, with greater than 20% purchase volume and member growth in 2024, Huang said. “We see attractive earnings power potential as Chime grows its consumer platform of 8.6 million members … affording the firm unique insights to extend compelling low-fee liquidity/lending products, which in turn drives increased loyalty and spending,” he wrote. Looking ahead, the company is on track to speed up the release of newer services such as liquidity products that give more members earlier access to more of their pay, he said. There are 13 analysts surveyed by FactSet who cover Chime; eight are bullish, four are neutral and one is bearish.
Hackers are resorting to brand impersonation to steal information or install malware by delivering logos and names to victims through PDF attachments in emails and persuading them to call “adversary-controlled phone numbers”
Hackers are reportedly impersonating brands like PayPal and Apple to steal information and send malware, according to recent research by Cisco Talos on a surge of instances in which victims call the scammers on the phone, responding to a request regarding an urgent transaction. “Brand impersonation is a social engineering technique that exploits the popularity of well-known brands to persuade email recipients to disclose sensitive information,” the researchers wrote. In these phishing scams, “adversaries can deliver brand logos and names to victims using multiple types of payloads. One of the most common methods of delivering brand logos and names is through PDF payloads (or attachments).” Many of these emails persuade victims to call “adversary-controlled phone numbers,” employing another popular social engineering tactic: telephone-oriented attack delivery (TOAD), otherwise known as callback phishing. Victims are told to call a number in the PDF to settle an issue or confirm a transaction. Once they call, the attacker pretends to be a legitimate representative and tries to manipulate them into sharing confidential information or installing malware on their computer.
Instacart’s rewards debit card lets its contract employees get free, automatic payouts of their earnings directly in their Shopper Rewards bank account for free after every batch they complete
Instacart has launched a rewards debit card for its contract “shopper” employees. The Instacart Shoppers Rewards Card, which debuted July 1 in partnership with workforce payments platform Branch, lets these workers get free, automatic payouts of their earnings. “We’re doubling down on our dedication to shopping excellence by empowering and rewarding shoppers who consistently deliver exceptional service to customers,” Daniel Danker, chief product officer at Instacart, said. “Instacart shoppers are shopping experts, and they balance efficiency, empathy and skill to serve their communities every day. Through the Cart Star refresh and the new Shopper Rewards Card, we’re recognizing and supporting their incredible work, while providing valuable resources to help shoppers thrive both on and off the platform.” The program lets shoppers have their earnings deposited directly in their Shopper Rewards bank account for free after every batch they complete. If these employees choose to use a different bank account, they’ll be charged $1.50 for the Instant Cashout service. Instacart will roll out the card to its U.S. shoppers in two phases, first in October, and again in April of next year. The card is part of Instacart’s Cart Star program
One Big Beautiful Bill Act offers advisors an avenue to be really proactive with their clients by sharing their thoughts and opinion on the bill’s massive impact on the rules for federal income taxes and estate planning
After President Donald Trump’s Republican allies raced to meet their July 4 deadline to pass the One Big Beautiful Bill Act, the legislation is on its way to be signed into law. Financial advisors and their clients can now take the rest of the year to plan for 2026 and beyond. The legislation extends and expands many provisions of the Tax Cuts and Jobs Act and will have a massive impact on the rules for federal income taxes and estate planning, alongside other Trump administration priorities such as defense and border security appropriations, work requirements for Medicaid beneficiaries and an increase to the debt ceiling. Trillions of dollars in additional federal debt as a result of the newly passed legislation pose further questions for investors. Over the next decade, the bill will expand deficits by $3.2 trillion, after savings of $1.4 trillion on the overall cost of $4.6 trillion, according to the Penn Wharton Budget Model. Beyond the political upshot and inevitable arguments around the economic impact of the legislation, advisors and their clients will likely want to prepare for an array of new tax rules coming into effect as early as this year. No matter their political bent or opinion on the law, it is “exciting that they can take advantage of something like that,” said Mike Byrnes, founder of advisor growth firm Byrnes Consulting. Since clients will no doubt be asking advisors’ thoughts, it makes a great topic for, say, a client or prospect event, he noted. “It just gives advisors another thing to be really proactive with their clients about,” Byrnes said. “Whether the client leans left or leans right, I think it’s a great opportunity to strengthen their relationship and just be in front of them.”
Fed cautions that invisible and embedded transactions may lead to overspending by making consumers and businesses lose track of spending, overlook transactions, or feel less in control of financial decisions
A posting by the Atlanta Fed cautions that invisible and embedded transactions may lead to overspending. When payments fade into the background, losing track of spending, overlooking transactions, or feeling less in control of financial decisions becomes much easier. On average, respondents find cash more helpful to prevent overspending and track their expenditures than electronic, and especially contactless, payment methods. When paying with cash, respondents are more aware of the exact amount that they pay. But as PYMNTS Intelligence has found, consumers and businesses across all verticals have been enthusiastically embracing frictionless commerce. Embedded transactions are fast becoming “table stakes” for providers, with 54% of independent software providers and 74% of marketplaces enabling digital payment experiences, a necessary step “to remain competitive.” “Embedded is the prefix for most of the innovations we talk about now in payments. We embed payments into software (something we’ve been doing ever since the dawn of eCommerce), identity into payments, lending into checkout flows, banking into virtual accounts, point solutions inside of tech stacks, GenAI into software, offers into banking apps, and networks into networks … A lot of what was called invisible at the dawn of the 2010s with the introduction of Uber is now described as embedded … But it’s not enough to just “embed” something into something else. Embedding should be almost invisible and frictionless.”
Capital One’s first multi-agentic workflow Chat Concierge, deployed through its auto business has improved their customer engagement metrics significantly — up to 55% in some cases
Milind Naphade, SVP, technology, of AI Foundations at Capital One, offered best practices and lessons learned from real-world experiments and applications for deploying and scaling an agentic workflow. Capital One recently launched a production-grade, state-of-the-art multi-agent AI system to enhance the car-buying experience. In this system, multiple AI agents work together to not only provide information to the car buyer, but to take specific actions based on the customer’s preferences and needs. With over 100 million customers using a wide range of other potential Capital One use case applications, the agentic system is built for scale and complexity. Capital One’s applications include a number of complex processes as customers raise issues and queries leveraging conversational tools. These two factors made the design process especially complex, requiring a holistic view of the entire journey — including how both customers and human agents respond, react, and reason at every step. “The main breakthrough for us was realizing that this had to be dynamic and iterative,” Naphade said. “If you look at how a lot of people are using LLMs, they’re slapping the LLMs as a front end to the same mechanism that used to exist. They’re just using LLMs for classification of intent. But we realized from the beginning that that was not scalable.” Based on their intuition of how human agents reason while responding to customers, researchers at Capital One developed a framework in which a team of expert AI agents, each with different expertise, come together and solve a problem. Additionally, Capital One incorporated robust risk frameworks into the development of the agentic system. As a regulated institution, Naphade noted that in addition to its range of internal risk mitigation protocols and frameworks,”Within Capital One, to manage risk, other entities that are independent observe you, evaluate you, question you, audit you,” Naphade said. The evaluator determines whether the earlier agents were successful, and if not, rejects the plan and requests the planning agent to correct its results based on its judgement of where the problem was. This happens in an iterative process until the appropriate plan is reached. It’s also proven to be a huge boon to the company’s agentic AI approach. “We have multiple iterations of experimentation, testing, evaluation, human-in-the-loop, all the right guardrails that need to happen before we can actually come into the market with something like this,” Naphade said. In terms of models, Capital One is keenly tracking academic and industry research, presenting at conferences and staying abreast of what’s state of the art. In the present use case, they used open-weights models, rather than closed, because that allowed them significant customization. That’s critical to them, Naphade asserts, because competitive advantage in AI strategy relies on proprietary data. In the technology stack itself, they use a combination of tools, including in-house technology, open-source tool chains, and NVIDIA inference stack. Working closely with NVIDIA has helped Capital One get the performance they need, and collaborate on industry-specific opportunities in NVIDIA’s library, and prioritize features for the Triton server and their TensoRT LLM. Capital One continues to deploy, scale, and refine AI agents across their business. Their first multi-agentic workflow was Chat Concierge, deployed through the company’s auto business. It was designed to support both auto dealers and customers with the car-buying process. And with rich customer data, dealers are identifying serious leads, which has improved their customer engagement metrics significantly — up to 55% in some cases. “They’re able to generate much better serious leads through this natural, easier, 24/7 agent working for them,” Naphade said.
New Liquid Foundation Models can be deployed on edge devices without the need for extended infrastructure of connected systems and are superior to transformer-based LLMs on cost, performance and operational efficiency
If you can simply run operations locally on a hardware device, that creates all kinds of efficiencies, including some related to energy consumption and fighting climate change. Enter the rise of new Liquid Foundation Models, which innovate from a traditional transformer-based LLM design, to something else. The new LFM models already boast superior performance to other transformer-based ones of comparable size such as Meta’s Llama 3.1-8B and Microsoft’s Phi-3.5 3.8B. The models are engineered to be competitive not only on raw performance benchmarks but also in terms of operational efficiency, making them ideal for a variety of use cases, from enterprise-level applications specifically in the fields of financial services, biotechnology, and consumer electronics, to deployment on edge devices. These post-transformer models can be used on devices, cars, drones, and planes, and applications to predictive finance and predictive healthcare. LFMs, he said, can do the job of a GPT, running locally on devices. If they’re running off-line on a device, you don’t need the extended infrastructure of connected systems. You don’t need a data center or cloud services, or any of that. In essence, these systems can be low-cost, high-performance, and that’s just one aspect of how people talk about applying a “Moore’s law” concept to AI. It means systems are getting cheaper, more versatile, and easier to manage – quickly.