We present the identification of potential members of nearby Galactic globular clusters using radial velocities from the RAdial Velocity Experiment Data Release 4 (RAVE-DR4) survey data base. Our identifications are based on three globular clusters - NGC 3201, NGC 5139 (ω Cen) and NGC 362 - all of which are shown to have |RV| > 100 km s-1. The high radial velocity of cluster members compared to the bulk of surrounding disc stars enables us to identify members using their measured radial velocities, supplemented by proper motion information and location relative to the tidal radius of each cluster. The identification of globular cluster stars in RAVE DR4 data offers a unique opportunity to test the precision and accuracy of the stellar parameters determined with the currently available Stellar Parameter Pipelines used in the survey, as globular clusters are ideal test-beds for the validation of stellar atmospheric parameters, abundances, distances and ages. For both NGC 3201 and ω Cen, there is compelling evidence for numerous members (>10) in the RAVE data base; in the case of NGC 362 the evidence is more ambiguous, and there may be significant foreground and/or background contamination in our kinematically selected sample. A comparison of the RAVE-derived stellar parameters and abundances with published values for each cluster and with BASTI isochrones for ages and metallicities from the literature reveals overall good agreement, with the exception of the apparent underestimation of surface gravities for giants, in particular for the most metal-poor stars. Moreover, if the selected members are part of the main body of each cluster our results would also suggest that the distances from Binney et al., where only isochrones more metal rich than -0.9 dex were used, are typically underestimated by ~40 per cent with respect to the published distances for the clusters, while the distances from Zwitter et al. show stars ranging from 1 to ~6.5 kpc - with indications of a trend towards higher distances at lower metallicities - for the three clusters analysed in this study.