Bühlmann–Straub (B-S) credibility assigns each account a weight , where is a single portfolio-wide ratio. The formula assumes is the same for every account regardless of size, history length, or volatility, and that recent and older years carry equal weight. On a held-out US commercial auto dataset these assumptions fail: standard B-S applied to 96 companies produces a calibration slope of 29 for small accounts, a signature of severe under-crediting. We propose a joint framework that retains B-S interpretability while addressing these limitations. The credibility weight is modelled as a logistic function of account characteristics; historical experience is discounted by an EWMA decay parameter estimated from the data; and , , and the complement are optimised in a single likelihood pass. The framework formally nests Bühlmann–Straub as a special case, admitting a likelihood-ratio test for any proposed extension. On a two-year held-out test set the proposed model restores calibration (slope = 1.00) and reduces exposure-weighted prediction error by 38% (90% bootstrap interval: 26%–50%). A size gradient in the decay rate emerges (, , for Small, Mid, Large) and replicates qualitatively on Other Liability. A simulation study confirms the mechanisms. The model requires only account-year summaries and delivers three transparent outputs: credibility weight, complement, and recommended renewal rate.

生成讲解博客的中文版本

生成AI智能校验的中文版本