Accounts Management “Balance Due” Call Transcript Classification
Description
This project aims to sort customer call transcripts into groups based on the issues customers need help with.
Detailed example
The AI system will output categories, classifying call transcripts.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
b) Pilot – The use case has been deployed in a limited test or pilot capacity.
Expected benefit
The AI system will inform research and decision making to enhance the customer experience.
Audit / financial statement impact
The output is not presumed to be high-impact and is not used as the principal basis for significant decisions/actions
Controls / human review
ATO: No; PIA: Not published
Data needed
Two datasets are used to fine-tune the model. The first dataset is the “NXT Switchboard Annotations”. This dataset has 260 hours of speech where researchers manually annotated calls for syntactic structure and disfluencies. Fine tuning is used to clean the call transcriptions. For the second dataset, project members manually labeled a dataset to train a classifier to identify and remove the identity verification portion of the call.