This paper discusses a new modality for speaker recognition - conversational biometrics - as a high security voice-based authentication method for E-commerce applications. By combining diverse simultaneous conversational technologies, high accuracy transparent speaker recognition becomes possible even in channel or environment mismatches. For speaker identification over very large populations, we combine dialogs to reduce the set of confusable speakers and text-independent speaker identification to pin-point the actual speaker. Similarly, dialogs with personal random or predefined questions are used to perform simultaneously knowledge-based and acoustic-based verifications of the user. Adequate design of the dialog allows to tailor the ROC curves to the needs of most applications. We demonstrate the conceptual advantages using our telephony prototype. Users familiar with the system can log into the system with 0.8% or 1.3% false rejection and ca. 5 • 10^−12% or 2 • 10^−6% false acceptance rates in about 40 sec or 20 sec respectively which is an impressive result as compared to purely voice-print based authentication.