David McGowan

Excited to share that Capital One has entered into an agreement to acquire Brex, a modern, AI-native software platform offering intelligent finance solutions that make it easy for businesses to issue corporate cards, automate expense management and make secure, real-time payments. https://bit.ly/3ZuzRgU

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With all of the other (mostly terrible) news we are being bombarded with, some potentially important stories are slipping into the background. Probably by design IMHO. While I remain skeptical of the ability of AI to deliver on it’s promises in the near to mid term, I could be wrong. And if “AI robots” start actually replacing human workers, the economic and societal impacts could be significant and well beyond the capabilities of government (especially proven corrupt incompetent governments) to deal with. https://lnkd.in/eaUcF_6Y

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AI Didn’t Buy My Car… But It Helped Me Save Thousands. My wife and I recently started shopping for a new car and had already decided our next vehicle would be electric. Like most buyers, we began researching options—but this time I used AI to speed up the process. We started by defining three lists: Show stopper was airconditions seats. Living in AZ I will never go back to not having this. Must Have • Fully electric • Strong battery warranty • Under $60K Nice to Have • Good range • Fast charging • Driver assistance features “That Would Be Cool” • Premium interior • Advanced infotainment We also had a trade-in: a 2020 Audi with about 26K miles. Instead of spending hours across review sites, I asked AI to generate EV options that fit our requirements. I still verified everything manually, but I was surprised how consistently accurate the results were. As our shortlist narrowed, I noticed one vehicle appearing frequently in the recommendations. To reduce bias, I started comparing answers across three AI tools: • ChatGPT • Microsoft Copilot • Claude Each offered slightly different insights, which helped validate the research. As we got closer to buying, I shifted my questions from research to strategy: • Best way to negotiate a car purchase • How to separate vehicle price from trade-in negotiations • How to navigate the finance office upsells The biggest benefit came during negotiation. AI helped me quickly check pricing, comparable listings, and negotiation tactics while sitting at the dealership. The biggest savings came in the finance office. We wanted strong warranty coverage—especially for the EV battery. Through AI-assisted research I found another dealer selling the same manufacturer extended warranty at wholesale pricing, saving over $3,000. The finance manager was skeptical when I mentioned the price—but the upselling stopped immediately. Using AI throughout the process: • Saved hours of research • Improved negotiation leverage • Saved thousands of dollars More importantly, it made me a much more informed buyer. I don’t think I’ll approach another major purchase without using AI as part of the research and negotiation process. Curious—has anyone else used AI during a major purchase or negotiation? #AI #Smartbuyer #Technology

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Why Fiserv $500M+ Acquisitions Wasn't Enought To Save Their Starving Core Business While the industry was networking during Money20/20, Fiserv's published numbers whipped out $30 billion in market cap, as they missed their Q3 expectations. But just 6 months ago, they were on a shopping spree buying up companies such as Payfare Inc., CCV, CardFree, and AIB Merchant Services. Over half a billion dollars spent buying companies to plug into Clover, their "pre-eminent small business operating platform." Meanwhile, the platform itself was falling apart. CEO Mike Lyons admitted it on the earnings call. They "deferred investments to boost short-term margins." Translation: they cut costs on the core business to make quarterly numbers look good while shopping for external growth. It gets worse. While acquiring companies to expand Clover's ecosystem, they were alienating existing Clover merchants with aggressive fee increases. Customers revolted. Management had to reverse the pricing, which tanked near-term revenue. So let me get this straight. You're buying growth externally while your internal operations are deteriorating? You're acquiring companies to integrate into a platform you're underinvesting in? And you're raising prices on the merchants you need to make the whole strategy work? That's not strategy. That's corporate ADHD. The numbers don't lie. Organic growth collapsed to 1% in Q3. Operating margins fell from 40.2% to 37.0%. Financial Solutions revenue declined 3%. And Argentina, which represented 10% of last year's growth, imploded. Acquisitions only work when you have operational excellence at home. You can't bolt on growth if the foundation is crumbling. Every dollar spent buying Payfare Inc. or CCV was wasted if Clover merchants are jumping ship because of poor service and unsubstantiated fee increases. Fiserv proved something important: M&A isn't a substitute for fixing your business. It's gasoline on a fire. If the fire is controlled, you get acceleration. If it's out of control, you get an explosion. The result? 44% drop in one day, and over $30 Billion in market cap lost. Analysts called it "impossible to sugarcoat" and "shocking." However, I don't believe this is the end of Fiserv, I think it is the necessary wake up call, that M&A without operational excellence is not a strategy. What do you think? Can Fiserv bounce back? Let me know in the comments. For more Payments Strategy check out my newsletter https://lnkd.in/e6eXZrF9

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In the SaaS control space, innovation is cheap. Engineering maturity is expensive. I’ve seen a pattern lately: less mature vendors are desperate to land Enterprise logos, but they’re bringing "startup-grade" engineering to "Global 500" problems. When you operate at the level of a GSIB, the stakes aren't just a bug in a dashboard—they are systemic risks to the global financial fabric. We’ve seen exactly what happens when SaaS vendors prioritize features over foundational engineering: ❌ The Sisense Compromise (2024): Hardcoded credentials in a self-managed GitLab instance allowed attackers to exfiltrate customer secrets and API keys. This is a classic "Engineering 101" failure—secrets should never live in code. ❌ The Okta Support Breach (2023/24): A service account in their support system was hijacked because it lacked MFA, allowing attackers to steal session tokens (HAR files) from high-value customers. ❌ The Snowflake Data Theft (2024): While technically "credential stuffing" on the customer side, the lack of enforced MFA and outdated "local-only" login options created a playground for attackers to hit over 160 companies. These aren't just "bad luck." They are the result of The Maturity Gap. If you are a SaaS vendor aiming for the Enterprise, "good enough" engineering will eventually get you—and your customers—hit. You need to close these three gaps: 1. Zero-Trust Internals: If your own developers or support staff have persistent, unmonitored access to customer data "just in case," you are a liability. 2. Hardened CI/CD: Hardcoded secrets and unencrypted logs are the first things a sophisticated actor looks for. 3. Verifiable Observability: If you can’t tell me exactly who touched my data and why within 5 minutes of an inquiry, you aren't ready for a regulated environment. To the startups out there: We want your innovation, but we require your maturity. If your engineering team is hitting a wall with Enterprise security requirements and you aren’t sure how to bridge that gap without killing your velocity—reach out. Let's build capability that actually earns the trust you're asking for. #CyberSecurity #SaaS #EnterpriseEngineering #SupplyChainRisk #Infosec

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Banks keep saying they want to grow with small businesses, but the market isn't waiting for them to catch up. SMBs are already financing themselves with expensive credit card debt, paying 18-36% interest on money that a traditional loan could provide at a fraction of the cost. That's not a small gap. That's a $130 billion opportunity walking out the door in real time. And the longer banks rely on slow, outdated underwriting processes, the more ground they lose to fintechs and alternative lenders who are already moving at the speed SMBs need. Some numbers are hard to ignore, and this piece from nCino had quite a few of them.

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