Snap Finance cuts AHT 40% and raises containment 5.5x with Cresta generative AI
Snap Finance was experiencing rapid growth and struggled to scale its contact center while managing costs and compliance. Reporting systems were inadequate and quality management relied on random call sampling, giving supervisors little visibility into overall agent performance.
Previous technology was described as anemic with major reporting problems, and quality management was effectively arbitrary—only a handful of random calls were reviewed each month.
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Cresta enabled Snap Finance to reduce average handle time by 40%, raise deflection rate from 6% to 33%, achieve 100% QA automation across all calls, and improve customer satisfaction by 23% along with employee engagement scores.
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Frequently asked questions
What did this team achieve with this AI workflow?
Cresta enabled Snap Finance to reduce average handle time by 40%, raise deflection rate from 6% to 33%, achieve 100% QA automation across all calls, and improve customer satisfaction by 23% along with employee engagem…
What tools did this team use?
Cresta, Virtual Agent, Agent Assist.
What results were reported?
Containment rate: 5.5x; CSAT: 23%; Average handle time reduction: 40%; Deflection/containment rate: from 6% to 33% (source-reported, not independently verified).
What failed first in this deployment?
Previous technology was described as anemic with major reporting problems, and quality management was effectively arbitrary—only a handful of random calls were reviewed each month.
How is this customer support AI workflow structured?
Customer contacts via voice or chat → Virtual Agent resolves digital inquiries → Agent Assist real-time prompts → 100% QA monitoring of all calls → Supervisor real-time coaching.
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