Regulators required Goldman to hold extra capital because risk was calculated two days after trades settled. I built the pipeline to generate risk in real time, at end of day, so that capital buffer was no longer needed.
Goldman's risk pipelines were slow. Trades would come in from dozens of business lines across the globe, each with their own systems and data formats, and by the time everything was collected, normalised, and processed, two days had passed. The firm was generating risk reports for trades that had already happened 48 hours ago.
Regulators saw this lag and required Goldman to hold additional capital as a buffer against that two-day window of uncertainty. That buffer sat at $1.2B — capital that was not working, not generating returns, just parked there because the firm could not show regulators an accurate same-day risk picture.
The fix sounds straightforward: speed up the pipelines. The execution was anything but. Trades came from dozens of different business lines, each running their own systems on their own schedules. Getting all of them to emit data fast enough to support same-day risk generation required rebuilding pipelines that nobody had touched in years, across teams that had no direct incentive to change.
The project had two distinct parts. First, building the data pipeline that could source trade data in real time from every business line. Second, building the risk manager tool that consumed that data and gave users something they could actually act on.
The engineering was hard. The product management was harder. This was not a project where someone handed me a spec and said build it. I had to figure out what to build, convince people who had no obligation to help me to help me, sequence work across three continents, and make tradeoff calls with incomplete information throughout.