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Ive spent much of my career in fintech, but some of the most inspiring innovations Ive seen came from a town most people have never heard of. In early 2025, Ipava State Bank, a tiny community institution in western Illinois, embedded a small amount of life protection into every eligible checking and savings account. No app to install, no portals, no extra stepscoverage was calculated from balances and capped per account. Six months in, reported results included $3.45 million in protection delivered, 7% deposit growth, 4.8% higher average balances, and a 25% increase in customers reaching maximum coverage levelsat a time when many peers were losing deposits. The program, developed in partnership with Wysh, is part of a growing wave of fintech innovation thats meeting people where they already areat their local banks and credit unions. For The National Alliance for Financial Literacy and Inclusion (NAFLI), its exactly the kind of progress we champion: Technology designed not just for scale, but for inclusion. Lets talk about why it workedand how other banks could adapt the idea without copying the setting. We worked alongside partners on this effort; here are five observations weve made about the projects design choices any institution can adopt. 1. Default-on beats opt-in. People dont lack interest in protection; they lack bandwidth. Making the benefit automatic eliminated friction and avoided the shame tax of apply if you can navigate the process. In low-adoption markets, behavioral simplicity is a strategy, not a shortcut. 2. Lead with the institutions trust, not the partners tech. The coverage showed up through the bank customers already relied on, which reframed the offer from a new product to learn to my bank is taking care of me. Community banks have a trust surplususing it thoughtfully matters more than adding another feature tile. 3. Translate the benefit to local risks. In Ipava, protection wasnt a perk; it mapped to single-income households, inherited farm debt, and small-business succession. Wherever you operate, write the value statement in the communitys language first, product language second. 4. Measure outcomes the customer can feel. Deposit growth is great; confidence is the point. Track balance stability, dormant-to-active reactivation, and share-of-wallet movements following benefit awarenesssignals that the relationships getting stronger, not just more expensive to promote. 5. Make branches the on-ramp, not the afterthought. Frontline staff need a 10-second script. For example, This account now includes a small layer of protectionautomatically and a two-minute FAQ guide. When the explanation is simple, you dont need an app demo to earn adoption. WHAT THIS CHANGES ABOUT FINANCIAL WELLNESS Most wellness programs ask people to learn more and do moredownload the app, change the habit, attend the webinar. The Ipava example flips that script: Make the institution do more so the customer doesnt have to. When protection is embedded where money already lives, inclusion stops being an aspiration and becomes the default state of the relationship. Thats the shift Wysh is helping banks unlockand the kind of design NAFLI believes can redefine what financial literacy looks like in practice. If your bank is ready to make this shift too: Dont over-engineer choice. In high-emotion categories, asking users to select multiple options underperform simple and common defaults. If possible, offer clarity, not a catalog. Dont outsource the story. Tech partners enable; the bank narrates. If customers dont hear it from you, they wont feel it from you. Dont chase app adoption as the goal. Adoption of the benefit matters more than adoption of the interface. Design to be understood in a branch foyer, not just a home screen. THE BIGGER INVITATION If community institutions want to win back deposits and relevance, they dont need shinier featuresthey need more visible care. The lesson from a small bank in western Illinois isnt that every place is Ipava. Its that trust-first, default-on design can work anywhere people still value a bank that shows up for their best daysand their worst. Maybe the bigger takeaway is simpler: innovation doesnt always look like new technology. Sometimes it looks like a familiar bank doing something timelessshowing up for people when it matters most. And thats why NAFLI is watching this movement closelybecause when fintech starts working for the people who dont download fintech, were finally getting somewhere. Edwin Endlich is the president and board chairman of The National Alliance For Financial Literacy and Inclusion.
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E-Commerce
All eyes were on Nvidias quarterly earnings announcement on Wednesday, as investors looked for signs of weakness indicating that the so-called AI bubble is about to deflate. In fact, Nvidia appears to be selling graphics processing unit (GPU) chips for data centers as fast as it can make them. On the call with analysts, Nvidia reported better-than-expected revenues of $57 billion for its October-ending quarter, a 62% increase over the same quarter last year. Revenues rose by $10 billion, or 22%, from the prior quarter. Perhaps most importantly, the company projected revenues of $65 billion in the current quarter. As a result, Nvidia shares rose 5% after the earnings were announced at market close on Wednesday. That bump created an additional $205 billion of market capitalization. Theres been a lot of talk about an AI bubble, Nvidia CEO Jensen Huang said in his opening comments on Wednesday. But from our vantage point, were seeing something very different. The bubble refers to the possibility that the stock prices and valuations of artificial intelligence companies have become disconnected from their earning potential. Investors also fear that the massive investments that Big Tech and AI companies are sinking into infrastructure like data centers wont be backed up by rapid AI adoption. Let me remind you that Nvidia is unlike any other accelerator companywe address every phase of AI, Huang said. Then he set out to show Nvidias current business within the context of some broad technological transitions that he says are happening all at once. Huang explained that business software that has traditionally run on CPUs is increasingly starting to run on accelerators, specifically the GPUs that Nvidia sells. He said many traditional business tasks are being done by generative AI systems, replacing classical machine learning for things like content suggestion, ad placement, and content moderation. He also said autonomous AI (such as self-driving cars) and AI agents (such as coding assistants) mark the beginning of yet another big transition: The transition to agentic AI is giving rise to new companies, new products, and new services. Our singular architecture enables all three of these transitionsacross all industries and all phases of AI, from cloud to enterprise to robots, Huang continued. In other words, Nvidia is set to ride these big waves to big-time chip sales well into the future. Worrying about a bubble today, he seemed to suggest, may be a little short-sighted. Company CFO Colette Kress said earlier in the call that both hyperscalers like Meta and Google, and top AI labs like OpenAI and Anthropic, continue to spend big on Nvidia chips. We are preparing for aggressive growth ahead and feel optimistic about our opportunity set, she said.
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E-Commerce
In planning meetings, in brainstorms, in the messy moments when decisions need to be made before all the information is in, AI is my copilot. But not in the cute robot helper way. I treat it like my sharpest strategist, fastest researcher, and most unflinching truth-teller. As the CEO of Quantious, a future-forward marketing agency that works with tech companies, my job is to stay fast, smart, and endlessly curious; not just for myself, but for my clients. Having executive-level AI by my side is how I operate at scale without sacrificing strategy or soul. Forget about the hype of AI. Lets talk about what it really takes to work smarter, experiment faster, and free up time to be a creative leadersomething that you cannot automate. 1. AI is my executive sparring partner When youre running a fast-growing company, youre constantly making judgement calls without all of the details. Most people want ChatGPT to flatter them. I want it to challenge me. I run new product ideas, positioning statements, and brand hypotheses through AI to surface the cracks I didnt see. I use it to model outcomes, debate assumptions, and yes, poke holes in the perfect plan I thought I had. Your team might be too polite to challenge you. AI wont be, if you train it well. Start every session with a persona, such as: You are my chief strategy officer. Your job is to challenge mediocrity and raise red flags. Train it over time by giving feedback: Thats too agreeable. Give me a sharper POV or This sounds like fluff. Get specific. And really push it to dig deeper instead of giving you a standard response: This idea solves the problem, but I dont think its the best solution. Push me toward something bolder or more efficient. How would someone with 10x my time/resources/experience approach it differently? You may be surprised where this back-and-forth can take you. 2. I use AI to protect my most valuable asset: Strategic attention The less time I spend on routine admin tasks, the more time I have to steer the ship. AI is my secret weapon for clearing out the clutter. I use Bluedot to record and transcribe meetingssaving me and my team hours in cleaning up and consolidating notes, and turning around recaps and next steps in minutes. And if I need a detail from the discussion, I can even query the transcript to get the info I need, and all the context around it. To start using AI for attention management, begin with one task you do often (summarizing docs, doing premeeting research, writing recap emails) and let AI take a pass. If you want to think strategically, you need space to think. AI gives it to you. 3. I never miss a market beat I don’t have time to read every analyst report or listen to every podcast (who does?!) but I need those insights. AI curates the signal from the noise. Perplexity Deep Research turns complex trend reports into briefs to share with my team, or even my clients. Waldo gives me market snapshots faster than a team of analysts. Ive also dabbled in AI-powered podcasts, which summarize the most important industry news so I can catch up while on the go. They supplement my other favorite podcasts, so Im always armed with the latest trends and biggest industry moves. 4. I baked AI into the org chart At Quantious, AI isnt a department. Its a utility, like Wi-Fi or electricity. Every team has access to tools like ChatGPT, Gemini, and Slack AI. Designers use it to explore creative variations. Ops uses it to document processes faster. Marketers draft content 10 times faster. The tech isnt the point. The enablement is. While not every team member taps into these tools on a daily basis, having them in the toolkit keeps the door wide open for experimentation. Ive said it before: AI has made remote work more productive, seamless, and well-documented. We dont just integrate AI into workflows; we integrate it into our collective intelligence. Because the point isnt to do more faster, it is meant to elevate how we operate, across the board. Remember, AI isnt the intern. Its your most strategic hire. The truth is: Your team doesnt need you to be a prompt engineer. They need you to be an AI-literate leader. AI is no longer a tool in your workflow. Its a seat at your table. Treat it like a trusted advisor, and youll make sharper decisions, faster, without sacrificing strategy or soul. Lisa Larson-Kelley is founder and CEO of Quantious.
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E-Commerce
Nvidia forecast fourth-quarter revenue above Wall Street estimates on Wednesday, betting on booming demand for its AI chips from cloud providers against the backdrop of widespread concerns of an artificial intelligence bubble. The results from the AI chip leader mark a defining moment for Wall Street, as global markets looked to the chip designer to determine if investing billions of dollars in AI infrastructure expansion had resulted in towering valuations that potentially outpaced fundamentals. The world’s most valuable company expects fiscal fourth-quarter sales of $65 billion, plus or minus 2%, compared with analysts’ average estimate of $61.66 billion, according to data compiled by the London Stock Exchange Group (LSEG). Shares of the AI market bellwether rose over 4% in extended trading. Ahead of the results, doubts had pushed Nvidia shares down nearly 8% in November, after a 1,200% surge in the past three years. The broader market has declined almost 3% this month. Still, analysts and investors widely expected the underlying demand for AI chips, which has powered Nvidia’s results since ChatGPT’s launch in late 2022, to remain strong. Nvidia CEO Jensen Huang said last month that the company has $500 billion in bookings for its advanced chips through 2026. Big Tech, among Nvidia’s largest customers, has doubled down on spending to expand AI data centers and snatch the most advanced, pricey chips as it commits to multibillion, multi-gigawatt build-outs. Microsoft reported a record capital expenditure of nearly $35 billion for its fiscal first quarter last month, with roughly half of it spent primarily on chips. Nvidia expects an adjusted gross margin of 75%, plus or minus 50 basis points, in the fourth quarter, compared with the market expectation of 74.5%. By Arsheeya Bajwa and Stephen Nellis, Reuters
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E-Commerce
Since beginning his second term in office, President Trump has taken a sledgehammer to climate action. His administration has made plans to expand offshore oil and gas drilling, canceled billions of dollars in clean energy projects, rolled back tax credits for electric vehicles, pulled the United States out of the Paris climate agreement, released a report that downplays the risks of climate change, and on and on. Climate experts have been vocal about the fact that Trump is setting back climate action, which puts the entire world at risk. The U.S. is the second-most polluting country in the world, behind only China. China, however, has been investing heavily in renewable power, and its total greenhouse gas emissions have been dropping as a result. Now, a new analysis by ProPublica and the Guardian attempts to quantify what that setback could actually look like. What the analysis found Trumps anti-climate policies could release so many extra greenhouse gases over the next decade that they could lead to as many as 1.3 million more temperature-related deaths globally, in the 80 years after 2035, the analysis found. That estimate covers heat-related deaths, minus the fewer deaths that will occur from cold temperatures. Already, heat is the leading cause of all weather-related deaths, and climate change has led to a noticeable uptick in heat related deaths. In the U.S. alone, heat-related deaths have increased by more than 50% since 2000, according to the Yale School of Public Health. The 1.3 million excess deaths does not include, the outlets note, the massive number of deaths from climate changes broader impacts, like droughts, floods, diseases, hurricanes, wildfires, and even lower crop yields. The number is, admittedly, a small figure when compared to the total number of deaths caused by temperatures changing because of climate change. A 2021 study on the mortality costs of carbon projected that, between 2020 and 2100, the planet will see 83 million temperature-related excess deaths under a business as usual emissions scenario. The ProPublica/Guardian analysis acknowledges this, but adds that the figure attributed to Trumps policies speaks to the human cost of prioritizing U.S. corporate interests over the lives of people around the globe. How the research was conducted To conduct the analysis, the outlets used scientific models to estimate how many additional emissions will be released into the atmosphere because of Trumps policies. They also took into account the mortality cost of carbon metric, which predicts temperature-related deaths from emissions. In responses to questions from ProPublica and the Guardian, the Environmental Protection Agency (EPA) contested the science underpinning their analysis, dismissing it as moral posturing. It added that the core calculation method ignores the dramatic uncertainties that dominate long-term climate projections. But climate scientists say the metric is valid, they report. Prior to Trump, we had the most ambitious climate policy that the U.S. has ever come up withour best effort to date by far of addressing this growing problem, Marshall Burke, an economist at the Doerr School of Sustainability at Stanford University, told the Guardian. When we roll these things back, he added, it is fundamentally affecting the damages were going to see around the world.”
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E-Commerce
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