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A long form discussion on the history of programming for quants at the banks from SAS to Python and the rise of machine learning. While the hype of machine learning changed some of the banking modeling practices the industry kept their head straight as regulators closely watched. Now in 2026 with the AI hype wave and regulators being less strict, the banks seem lost as many are calling to replace SR 11-7 with general frameworks to reduce risk management and drive more efficiency. While this sounds good from a profit perspective, it is throwing out common definitions of models in a chase for non-sense.

Balancing the hype and trends also has been hard with the YouTube channel. It is much easier to sell snake oil as everyone wants a magical cure to profit, high salaries, minimal work, programming, math, and stats without putting in any work. I have done fairly well at sticking to creating real quant educational materials and industry perspectives even when passing up easy growth opportunities. Ten years later and we passed 100k subscribers without selling out.

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