Over the past few years, market researchers working with data from nonprobability online panels have voiced a number of data quality concerns over issues such as respondent identity, increased satisficing, and possible professionaliza-tion. While recognizing the importance of having real, unique, and engaged panelists, panel companies are responding to these issues by introducing a variety of remedial measures such as name-address verification, email address verification, and validation of key demographic information against third-party databases. This study describes one such effort. In this study, for a cross-section of new members who were recruited online, we validate their identity and self-reported information against multiple data aggregators and identity verification vendors to identify patterns of matches and mismatches. In addition to conducting a cross-vendor comparison of match rates and assessing differences between matched and mis-matched sample portions, we conduct multivariate analysis of match rate at various levels (i.e., vendor, sample groups, etc.). Results reveal a high identity match rate across all vendors with interesting relationships (ex. with panel activity and member age). While match rates for self-reported information were modest in general, the effect was more pronounced for certain demographic groups. This study is likely to have important implications for the data quality aspects of online panel recruitment, participation and retention.