A product team asks an ML engineer whether to build a rule-based fraud detector or an ML model. Transaction patterns are well-understood by domain experts, rules have been stable for 18 months, and the existing rule engine's false-positive rate is acceptable to the business. What is the strongest argument for keeping the rule-based system?