UK financial regulators are experimenting with the conversion of rulebook content into machine-readable and executable code. A major driver of these initiatives is the belief that the use of algorithms will eliminate the need for human interpretation as a deliberative process, and that this would be a welcome development because it will improve effectiveness while cutting time and costs for regulators and the industry alike. In this article, I set out to explain why human interpretation should be preserved and further harnessed if data-driven governance is to work at all. To support my thesis, I bring attention to the limited translatability of rulebook content into code, and to the difficulties for machines to engage with the full spectrum of tasks of analogical reasoning. I further contend that it would be desirable to preserve human interpretation on procedural grounds pertaining to the legitimacy of financial regulators. I conclude with recommendations about the future design of the financial rulebooks.