call_center_ai · finance · workflow
Fortune 500 Financial Services Firm Automates Customer Sentiment Index and Customer Effort Impact Using Verint Speech Analytics
A Fortune 500 financial services firm handling approximately nine million calls annually lacked an automated means to quantify customer sentiment and effort pain points, making it difficult to prioritize customer experience improvement initiatives.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Call ingestion trigger
The contact center handles approximately nine million calls annually, providing the raw voice data input for sentiment analysis.
Tools used
Verint Speech Analytics
Outcome
The firm now has automated, month-over-month visibility into customer sentiment and effort trends by call driver, and has translated those insights into process improvements — including modified agent scripts, web self-service offers, CRM authentication changes, and targeted training — to mitigate excessive average handle time and reduce repeat calls.
Results
Time savedMitigates excessive average handle time
Volume60 percent
Grounding & classification
Source type: vendor customer story
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sentiment analysiscall recordinghuman review describedmetric backedproduction runtime claimedsource backedtools describedworkflow describedfinancial servicesinsurancecustomer satisfactioncycle time reductionresolution time reductionvendor customer storycall center aicustomer supportquality assuranceextract classify routemonitor detect alert