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Currently, catastrophe models used by the insurance industry account for liquefaction simply by applying a factor to shaking-induced losses based on local liquefaction susceptibility so there is a need more sophisticated approach to incorporating the effects of liquefaction in loss models is needed. This study compares eleven unique models, each based on one of three principal simplified liquefaction assessment methodologies: liquefaction potential index (LPI) calculated from shear-wave velocity; the HAZUS software methodology; and a methodology created specifically to make use of USGS remote sensing data. Data from the September 2010 Darfield and February 2011 Christchurch earthquakes in New Zealand are used to compare observed liquefaction occurrences to predictions from these models using binary classification performance measures. The analysis shows that the best performing model is the LPI calculated using known shear-wave velocity profiles, although this data may not always be available to insurers. The next best model is also based on LPI, but uses shear-wave velocity profiles simulated from the combination of USGS VS30 data and empirical functions that relate VS30 to average shear-wave velocities at shallower depths. This model is useful for insurance since the input data is publicly available. This paper also considers two models (HAZUS and EPOLLS) for prediction of the scale of liquefaction in terms of permanent ground deformation but finds that both models perform poorly and thus potentially provide negligible additional value to loss estimation analysis outside of the regions for which they have been developed. [ABSTRACT FROM AUTHOR]