Hi everyone,
We're currently designing a voice-based identity verification experience in Genesys Cloud and would appreciate some guidance on the recommended architecture.
Our goal is to verify a caller before they reach an agent. The information we need to validate is:
- ID number
- Full name
- Date of birth (DOB)
Because DOB is sensitive, we don't want it to be stored or exposed in transcripts, so we're planning to collect it in a Secure Call Flow.
Our current thinking is:
- Inbound Call Flow
- Call Bot Flow to collect the ID number and full name
- Store these values as Participant Data
- Return to the Inbound Call Flow
- Transfer to a Secure Call Flow
- Retrieve the Participant Data
- Collect DOB securely
- Call a Data Action to validate the details
- Transfer to ACD
One concern we have is capturing full names accurately. In a previous project, we built a voice bot that routed callers to different phone numbers, and we found that speech recognition for names could be inconsistent, particularly with Australian and international names.
I'm interested to hear how others have approached this.
- Do you capture the caller's full name by voice, or do you avoid this altogether?
- Would you recommend looking up the caller by ID number first and then asking them to confirm the retrieved name instead of asking them to speak it?
- Has anyone implemented a similar Bot Flow → Secure Call Flow design for identity verification?
- Are there any best practices or lessons learned that you would recommend?
- For this type of identity verification use case, would you recommend a Bot Flow or a Virtual Agent (VA), and why? Also, is there a better overall approach than the architecture we've outlined above?
Thanks in advance for any advice or suggestions!
#ConversationalAI(Bots,VirtualAgent,etc.)------------------------------
Phaneendra
Technical Solutions Consultant
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