Local investors have officially surpassed builders in adding new housing supply in many markets, according to a new report from New Western. In 2025, investors have brought 30,852 renovated single-family homes back to market in New Western coverage areas — far exceeding the 18,973 new builds sold this year. Kurt Carlton, co-founder and president of New Western, told the imbalance is striking. “There’s a huge need for affordable housing, and the builders can’t supply it, but we have 15 million vacant homes,” he said. “They’re highly educated, corporate refugees that have left high incomes, looking for something more autonomous, and they’re taking those management skills, rehabbing these houses and bringing them back to the market. Some are making income beyond what they were seeing in the corporate sector. Institutional investors accounted for only 1.93% of all home purchases in Q1 2025 and just 6.6% of investor purchases, down 62% from their 2021 peak. Most operate close to home — with 68% investing within 30 miles of where they live. About 78% plan to purchase just one to five properties in the next year. Carlton argued that policymakers don’t yet grasp the role these small investors play. The Neighborhood Homes Investment Act would create a federal tax credit to build and rehabilitate affordable homes for urban, suburban, rural and tribal communities. More than 70% of revitalized homes are purchased off-market — never showing up in MLS data, according to the report. Carlton said the omission distorts the picture. There’s a million that are off-market. These are generally not habitable. It’s the type of house that a local real estate investor really needs to buy and revive.” Revitalized homes typically re-enter the market at significantly lower price points than both existing homes and new construction. The report found the average existing home sale price was 54% higher than the average revitalized home — and the median existing home price was 17% higher. Compared to new builds, revitalized homes are often 35% to 80% less expensive. “It’s really challenging for builders to supply affordable inventory in the areas that need it,” Carlton said.
For investors integrating generative AI into asset management, best practices are structured internal data, prompt engineering, targeted workflows focused on specific use cases, and vertical AI champions in departments such as equities and fixed income
Bernstein Research has identified 10 best practices for investors integrating generative AI into asset management, emphasizing the importance of structured data, targeted workflows, and measurable outcomes. The brokerage emphasizes the need for clean, structured internal data, prompt engineering, centralizing data, breaking down daily workflows into specific use cases, and developing vertical AI champions. To scale AI effectively, firms should prioritize top use cases, structure offsite exercises, and engage in regular knowledge-sharing sessions within teams. Developing vertical AI champions in departments such as equities, fixed income, legal, or compliance ensures solutions remain close to real use cases. Dedicated AI talent is also needed, with some firms assigning specific team members to focus on AI tools or hiring external specialists. Tools like Daloopa and ModelML are cited for model automation and internal data integration. Early engagement with implementation partners or adopting ready-made AI tools can speed progress without requiring deep technical expertise. In the future, organizations should prepare to work with hybrid teams of humans and artificial intelligence, requiring robust data infrastructure and governance. Clear metrics to evaluate Gen AI’s impact include operational efficiency, error rate reduction, time to generate insights, volume of AI-generated ideas, and comparisons with human output. Success in portfolio management can be assessed by time saved during scenario analysis and the frequency of bias avoidance in decisions post-AI implementation.
JPMorgan says ETF and treasury demand propel Ether as funds draw near‑bitcoin July inflows; prospects of SEC‑permitted staking of spot ETF will unlock mainstream yield access
Ether (ETH) has outperformed bitcoin (BTC) over the past month, buoyed by strong inflows into spot exchange-traded funds (ETFs) and growing corporate treasury allocations, Wall Street bank JPMorgan (JPM) said in a report. The move comes in the wake of U.S. stablecoin legislation (the GENIUS Act) and ahead of an anticipated vote on a broader crypto market structure bill by the end of September, the report said. In July, spot ether ETFs saw record inflows of $5.4 billion, nearly matching bitcoin ETF inflows over the same period. While bitcoin ETFs have posted modest outflows in August, ether funds continue to attract capital, JPMorgan noted. The bank’s analysts pointed to four main factors behind ether’s recent strength. Investors are betting the Securities and Exchange Commission (SEC) will eventually permit staking for spot ether ETFs, which would turn them into yield-generating products while lowering technical barriers for participation. Corporate demand is also rising, the analysts noted, with about 10 publicly traded firms now holding ether equal to a total of 2.3% of the circulating supply. Some of these companies may seek additional income through staking or decentralized finance (DeFi) strategies. JPMorgan suggested ether holdings in both ETFs and corporate treasuries could rise further, pointing to bitcoin’s higher share of circulating supply locked up across both categories as a benchmark.
Buffered ETFs gaining traction by offering partial downside protection, that shields investors from a set percentage of losses, typically 10% to 20%, over a fixed period in exchange for capped gains, with the terms reset at the end of each outcome window
Buffered ETFs, also known as defined outcome products, have gained traction in recent years by offering partial downside protection in exchange for capped gains. Each fund is structured to shield investors from a set percentage of losses, typically 10% to 20%, over a fixed period. In return, gains are limited, and the terms reset at the end of each outcome window. Buffered ETFs struggled to gain traction after their late 2018 debut — and for good reason. From 2019 through 2021, the S&P 500 returned an average of 24% annually, leaving little appeal for products that cap upside. But a sharp downturn in 2022 changed the equation. With the index falling nearly 20% that year, investors poured nearly $10 billion into buffered ETFs, breathing new life into the once-overlooked product. During times of declining equities, investors often rely more heavily on bonds. But in recent years that strategy hasn’t always worked out, according to Charles Champagne, head of ETF strategy at Allianz Investment Management. “When you have an equity and fixed income portfolio, if equities are in a tougher market, you expect your fixed income to offset those losses, and that just really hasn’t happened in the past [couple of years],” Champagne said. “So these products really help in that capacity.” To build buffered ETFs, issuers like Allianz use options to shape both downside protection and upside limits. They start by buying a deep-in-the-money call to mirror market exposure. Then, to create the buffer, they buy an at-the-money put and sell an out-of-the-money put, defining how much loss the fund will absorb. To offset the cost of this protection, they sell a call option, which in turn sets the cap on gains. This options mix allows issuers to offer defined outcomes over a set time frame, typically one year.
AI-powered AI “sandboxes” let advisors pre‑test client reactions with synthetic demographics, agentic AI, and compliance‑ready guardrails before campaigns or pricing go live
The emerging world of AI-powered simulation sandboxes could provide an opportunity test how a client would react to a message before it’s even sent. With AI simulation sandboxes, which EY Consulting’s Sameer Munshi, head of behavioral science and simulation, compared to crystal balls, advisors can “recreate” any demographic in the world via synthetic data and agentic AI. “It’s recreating the parameters of a human,” he said. “It’s decoding human behavior based on how you describe it.” Once that simulation is set up, Munshi said advisors can interact with these “people” in a qualitative conversation, posing targeted questions in order to test what messaging — or even a new price point — resonates with a particular client population. The immediate benefits of the AI simulation sandbox are obvious, said Munshi. “The power of this technology is understanding what investors or consumers actually want, even if it’s not a perfect correlation to what exists today from a research perspective,” he said. “The fact that you can get it in days instead of months is going to completely change how we think about research.” Compliance is an important use case for AI-powered simulation environments, said William Trout, director of securities and investments at technology data firm Datos Insights. In terms of investment suitability, simulations could test portfolio recommendations against diverse client profiles, ensuring recommendations truly serve client interests rather than advisor compensation structures, he said. The next step for firms considering adoption of these sandboxes is to begin with a narrow pilot program that uses nonsensitive data. For example, an advisory team could test how an AI-generated client reacts to a quarterly market commentary before distributing it. While AI adoption among financial advisors has increased dramatically in 2025, the specific concept of comprehensive simulation environments for testing client reactions is “pretty nascent,” said Trout, who has not seen many deployed use cases for AI-powered simulation sandboxes in wealth management. Such sandboxes enable risk-free experimentation with client interactions, marketing strategies and portfolio recommendations in controlled environments, said Trout. “They accelerate client growth by helping advisors identify high-potential prospects and refine outreach strategies that improve conversion rates and retention,” he said. “Enhanced productivity comes from offloading routine tasks like meeting preparation, follow-ups and client research to AI agents, allowing advisors to focus on high-value relationship building and strategic planning.” Another example of how advisors can use sandboxes is determining whether to raise fees, and if so, how much, said Munshi. Advisors can also use the technology to decide how to invest in ads, said Munshi. The sandboxes also provide continuous learning opportunities through data generation that trains models and refines strategies over time, said Trout.
Community banks offering digital estate planning tools are establishing a brand connection with next-gen heirs, by offering to gather and store family videos and photos
A massive generational wealth transfer is underway, with heirs moving inherited assets away from community banks 70% of the time — threatening deposit stability as over $30 trillion changes hands by 2030. Community banks are adopting digital estate planning tools — like Thomaston Savings Bank’s partnership with Paige — to help families prepare proactively and help banks retain relationships with the next generation. Adding Paige allowed the bank to scale estate planning services and make guidance more accessible. When community institutions help parents plan, and since they have the largest share of that age group, removing bad experiences enables banks to transition from a reactive to a supportive role in the estate for the next generation. Through its Paige partnership, Thomaston Savings is also doing more than covering the practicalities of estate planning; they’re reaching deeper into the relationship to establish a brand connection. Customers of Thomaston Savings can get a head start on gathering and storing family videos and photos. They can even schedule a calendar of messages for loved ones to receive in the years after they are gone. (All of these services are offered through one discounted subscription to depositors and provided via a cobranded portal from the bank’s website.) It’s not a deposit service, but community institutions are turning to partners for differentiation – especially when up against the largest nationwide banks – in services at “the edge on money,” as Alloy Labs Alliance CEO Jason Henrichs describes it. It’s about deposit effects created “looking beyond the account and the transactions for new ways to create value for the customer,” he says. “That can require partnering with technology companies that didn’t start out pursuing bank partnerships. They’ve built valuable services that created new value for customers and the banks.” Since it launched, Paige has also partnered with the American State Bank, as well as Claremont Savings Bank. These technology companies “give the service to the banks for free,” says Josh Seigel, Chairman and CEO of StoneCastle Partners, and also an investor in Paige. “There’s really no process other than vendor due diligence for banks. Customers can use this service and pay a monthly fee of approximately $2; it’s intended for individuals who don’t have an estate attorney.
Advisor CRM debuts a GenAI marketing suite that drafts LinkedIn posts, emails, and client letters in an authentic voice while automating segmentation and scheduling
Advisor CRM has launched its Gen AI Marketing Suite, a fully integrated set of free and paid tools empowers advisors to automate content creation, streamline marketing workflows, and strengthen client relationships. The Gen AI Marketing Suite includes Agents for generating Facebook and LinkedIn posts, marketing emails, client letters, press releases, and more—with new tools added weekly. With minimal training, the AI quickly learns an advisor’s tone of voice, unique value proposition, and communication style, enabling it to write marketing copy and client communications in the advisor’s authentic voice. Key features of the Gen AI Marketing Suite include: AI-powered email creation – Draft messages from scratch or with AI assistance, including suggestions for subject lines, tone, and clarity. Authenticity at scale – With minimal training, the AI learns your style and unique value proposition, writing copy in your authentic voice. Smart segmentation – Organize contact lists with custom tags (e.g., high-value clients, VIPs, new clients). Scheduling & automation – Plan email campaigns in advance with seamless scheduling tools. “Advisor CRM’s Gen AI Marketing Suite turns hours of marketing work into minutes,” said Ryan Borer, Managing Partner at Advisor CRM. “By leveraging AI, we’re not only making content creation easier but also ensuring it’s brand-consistent and client-ready. Because the system adapts to each advisor’s voice and value proposition, the marketing content it generates feels authentic, personal, and true to the advisor’s brand.”
Broadridge’s integration of Uptiq’s tech into its wealth management platform provides advisors access to agentic AI apps that surface the most relevant loan options, automating securities-based lending- (SBL) workflows, referral submission and covenant tracking
Broadridge Financial Solutions has announced a strategic partnership and minority investment in Uptiq, an AI platform for financial services. The partnership aims to modernize wealth management by addressing the growing demand for artificial intelligence in financial services and developing a better wealth lending process. Uptiq’s AI-powered tools and Broadridge’s Wealth Lending Network will enable advisors to deliver smarter lending recommendations, save time, and help clients access the liquidity needed to achieve their financial goals. The integration will streamline the process of accessing securities-based lending solutions, particularly for financial advisors and wealth management firms not affiliated with banks. Broadridge’s investment supports Uptiq’s growth and reinforces a shared vision for transforming wealth lending.
Halo Invest’s platform for advisers offers a light-touch, client-administrated option to efficiently service customers with more modest assets allowing them to easily check progress for clients and corporate actions
Halo Invest Adviser Gateway is now live, offering advisers a light-touch, client-administrated option to efficiently service customers with more modest assets. The platform, led by CEO Douglas Boyce, has secured its first advice firm client and a strong pipeline of new business for the immediate future. The platform is built to make investing “simpler, fairer and better” through innovative functionality, including a transfer dashboard for advisers to easily check progress for clients and corporate actions that the adviser doesn’t need to respond to individually. It also uses Go Cardless for efficient client money addition. The platform features include onboarding, trading, custody, and reporting, as well as a comprehensive range of investments and wrappers. The senior management team at Halo Invest has close to 200 years of combined experience within financial services, including former Tatton CEO Helen O’Neill, Head of Risk and Compliance Wendy Crawford, and Head of Customer Lynn Johnston. Halo Invest Adviser Gateway represents an evolution rather than a revolution, helping advisers achieve profitability from parts of their client book where it was previously difficult or impossible.
eToro’s AI tools to enable retail traders to develop bespoke trading algorithms, automate trade execution with precision and interact with social feed via customizable boiler plates and rich media posts creating a community-led marketplace for investing
eToro is launching a suite of AI-tools that will transform social investing by creating a community-built marketplace for investing built on top of eToro’s new public API. This marks a significant leap forward in the democratization of investing, arming retail traders and investors with sophisticated, AI powered capabilities previously only accessible to quantitative hedge funds. The suite of AI-tools will initially be available to eToro’s Popular Investors, a subset of users who are a vetted group of top traders and investors who meet specific criteria and whose investment strategies can be copied by other users via eToro’s patented CopyTrader technology. The key capabilities which will be deployed include the ability to: Develop bespoke trading algorithms and automate strategies; Automate trade execution: AI-driven algorithms to execute trades with precision, minimizing latency and maximizing efficiency; Integrate real-time market data and third-party tools, including backtesting and advanced analytics, to identify trends and opportunities across stocks, crypto, and ETFs, in order to build investment strategies; Personalize portfolio optimization: Tailored recommendations based on risk profiles, market conditions, and user behavior; Create personalized dashboards for monitoring portfolios and market activity including sophisticated risk management tools, powered by AI including Value-at-Risk (VaR) analysis and portfolio stress testing; Interact with eToro’s social feed via customizable boiler plates e.g. rich media posts. eToro’s focus on AI-empowerment, includes the launch of Tori, eToro’s next-gen AI companion. Tori is a powerful AI assistant transforming how users interact with eToro: answering questions, surfacing personalized insights, guiding them across the platform, and helping them better understand the world of investment – all through natural conversation.