Customer Service Automation · Security and Compliance
ExpertSource needed to monitor far more call-center interactions for compliance because manual review of only a small sample left the company exposed to regulatory penalties, litigation and inconsistent service quality in debt-collection operations.
Reported impact
ExpertSource expanded monitoring from a tiny sample to full coverage, improved collections performance, reduced legal risk and gave managers much more scalable visibility into agent compliance and service quality.
ExpertSource expanded its CXReview automated call-review platform through a co-creation project with IBM Client Engineering, turning keyword-based compliance monitoring into a cloud-native ML workflow. The solution runs in Kubernetes containers on Red Hat OpenShift and uses an embedded IBM service agreement to call IBM Watson Studio, IBM Watson Machine Learning, Speech to Text and Natural Language Understanding against recorded calls. Audio is transcribed, analyzed for natural-language meaning and checked against compliance requirements rather than simple keyword presence, allowing far broader monitoring coverage across the collections operation. Because the stack is deployable on public or private cloud, CXReview could keep evolving the platform while giving ExpertSource production-ready analytics in a short timeframe. The result is a scalable compliance pipeline that continuously evaluates calls, supports quality teams and reduces dependence on expensive manual sampling.
Recorded calls are transcribed with Speech to Text, analyzed with Natural Language Understanding and Watson ML services, evaluated inside CXReview against compliance rules, and surfaced to quality teams through the OpenShift-hosted platform for broad, automated call monitoring.
"100% of calls can be monitored without increasing headcount"
"280,000 separate compliance checks can be carried out daily"
"Since we started working with CXReview, we've gone from 2% to 100% monitoring."
"The CXReview solution runs in Kubernetes containers on any public or private cloud"
"using Speech to Text Natural Language Understanding models to analyze call recordings and check them against compliance requirements"
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Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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