As well-known, the benefit of restricting to Lévy processes without positive jumps is 1 the "W, Z scale functions paradigm", by which the knowledge of the scale functions W, Z extends 2 immediately to other risk control problems (see for example [1-5]). The same is true largely 3 for strong Markov processes X t , with the notable distinctions that a) it is more convenient to 4 use as "basis" differential exit functions ν, δ introduced in [6], and that b) it is not yet known 5 how to compute ν, δ or W, Z beyond the Lévy, diffusion, and a few other cases. The unifying 6 framework outlined in this paper suggests however via an example that the spectrally negative 7 Markov and Lévy cases are very similar (except for the level of work involved in computing the 8 basic functions ν, δ). We illustrate the potential of the unified framework by introducing a new 9 objective (33) for the optimization of dividends, inspired by the de Finetti problem of maximizing 10 expected discounted cumulative dividends until ruin, where we replace ruin by an optimally chosen 11 Azema-Yor/generalized drawdown/regret/trailing stopping time. This is defined as a hitting time 12 of the "drawdown" process Y t = sup 0≤s≤t X s − X t obtained by reflecting X t at its maximum 13 (see [7] for an application to the Skorokhod embedding problem, and [8-11] for applications to 14 mathematical finance and risk theory). This new variational problem has been solved in the parallel 15 paper [12]. 16