Hard Collection Voice Analytics
- Reviewed
- 41 contacts
- 20 calls and 21 field visits
Task: find out whether collection operators follow the script — listening to every call by hand is impossible.
How it works
- 0101 · InputA call or a visit: the recording and the visit report
- 0202 · TranscriptionThe dialogue into text with the speakers separated
- 0303 · ComparisonA six-step script: what was covered, what was skipped
- 0404 · EvidenceQuotes from the conversation: a real phrase under every conclusion
- 0505 · ResultA KPI dashboard: operator cards and summary metrics
WHAT THE MODEL ASSESSES — script steps covered and skipped · the tone of the conversation · breaches of the regulations — with a quote from the transcript under every conclusion
Particulars and difficulties
Nobody will believe the model’s verdict
So the LLM returns quotes: a manager checks the conclusion against the text of the conversation, not on trust
A conversation does not follow the paper
A script step can be completed in other words — the comparison works on meaning, not on matching phrases
A sensitive area
Collection is regulated: besides the steps, the system marks tone and breaches in dealing with the debtor
Showing it without access to the contour
Real calls and visits are baked into the image: the demo starts with one command, with no client integrations
Results
- 100%
- of contacts reviewed, not a sample
- 6
- script steps under control
- 41
- calls and visits in the review
Training on facts, not impressions
An operator’s card shows which step they systematically skip
Every conclusion can be contested
A quote next to the assessment removes the “the model made it up” argument before it starts
Stack
Flask · OpenRouter · Docker