19 posts tagged with "Community Bank"

I came into banking from the outside, a builder used to moving fast and questioning why things worked the way they did. I carried a stack of assumptions with me. Most of them turned out to be wrong, or at least incomplete. Looking back at where I started and where I am now, the gap between the two is the truest measure I have of what this stretch taught me.

People have been predicting the end of community banks for as long as I have been paying attention. Too small to compete, too slow to modernize, about to be swallowed by the big banks or routed around by fintechs. The pressures behind those predictions are real. And yet the obituary keeps turning out to be early. Having spent time in this part of the industry, I have come to see why, and what tends to set the community banks that endure apart.

For a few years, Banking as a Service looked like the rare arrangement where everyone won. Fintechs got to offer bank accounts without a charter, small banks got fee income and a foot in the digital door, and the people using the apps got slick products. I wanted that arrangement to work. Years ago, when I was building a payments product, a partnership like this was exactly what I was looking for and couldn't get. So when the model started breaking in the most visible way possible, I paid close attention, this time from inside a bank rather than outside trying to get in.

For a while now, operations has struck me as the place where technology could do the most good inside a community bank. Not the headline projects. The day to day work of serving clients and moving loans through the pipeline. The easy assumption is that more automation is the goal in itself. I see it differently. The point of operations technology is to make the bank faster, more responsive, and easier to work with, for clients and for the people serving them. That is a different target than automation for its own sake.

Most of the conversation about data strategy at a community bank ends up in the wrong place. People want to talk about tools, vendors, dashboards, the latest architecture. The harder problem is sitting one floor up. The people making decisions do not need more data. They need a small set of things they can act on, and they need it consistently.

FedNow went live on July 20 with 35 certified institutions. After decades of batch-processed payments, the Federal Reserve now has its own instant payment rail. I've been waiting on something like this for a while, and I'm already turning over what it means for community banks.

A month out from the SVB collapse, the immediate panic has subsided but the lessons haven't. The biggest one for me is a distinction that sounds simple but changes how I think about risk. SVB was well-capitalized. It ran out of cash. Those are two very different problems.

Silicon Valley Bank failed on Friday in roughly 48 hours. Watching this play out from the inside of the banking industry, what stood out was the speed and how cleanly the mechanics matched what the risk frameworks have always warned about.

Watching what rising rates have done to bank securities portfolios over the past year got me looking into the broader question. Unrealized losses on bonds are one thing. The bigger question is how rate movements affect an entire balance sheet, not just the securities line. That's what interest rate risk actually is, and I've been spending time trying to understand the framework bankers use to manage it.

I've spent the last two months on personal time exploring ChatGPT, digging into how large language models work, and running it through every banking scenario I can think of. The wonder phase is fading. What's replacing it is a more practical question. Where could this eventually help at a community bank, and where would it get a bank in trouble?