Quality Assurance (QA) teams are under constant pressure to review large volumes of calls, ensure compliance, and maintain consistent customer experience. For a global bank handling millions of customer interactions each month, this challenge had reached a breaking point.
Manual call auditing was slow, inconsistent, and unable to provide insights at the speed the business needed.
This case study explores how the bank partnered with Daisee to automate their QA operations and successfully reduce review time by 70%, while improving the quality and accuracy of analytics.
The bank faced several issues within its contact centre QA operations:
Only 2–3% of calls were being manually reviewed, leaving blind spots in compliance and customer experience.
Analysts spent hours listening to calls end-to-end, manually identifying issues and filling audit forms.
Different auditors interpreted call quality differently, resulting in score variation and disputes.
The bank could not detect compliance breaches, risk signals, or customer sentiment until weeks later.
They needed a solution that could analyze 100% of calls, highlight issues instantly, and free QA teams from manual work.
The transformation was rolled out in three main phases:
Daisee’s team analyzed the bank’s scripts, compliance requirements, and existing QA scorecards.
AI models were trained using the bank’s real customer conversations across multiple products including loans, credit cards, and savings.
Daisee was integrated into their existing contact centre platform, enabling:
Within weeks, the bank began seeing measurable improvements.
The transformation was rolled out in three main phases:
Every call was automatically analyzed — eliminating data blind spots.
AI-driven scoring removed subjectivity and produced consistent results across all teams.
Risky interactions that previously took weeks to identify were now detected in real time.
Supervisors used Daisee’s insights to coach agents based on real behaviour patterns, improving customer satisfaction.
“Daisee has transformed how we manage quality. Our team no longer drowns in manual reviews — we focus on high-risk calls instantly. The accuracy and speed of insights have changed the way we operate.” — Head of Contact Centre Operations, Global Banking Client
Automating QA allowed the bank to shift from reactive, manual auditing to proactive, insight-driven quality management. With Daisee, the bank now operates faster, more accurately, and at a scale that was impossible with traditional methods.
This case demonstrates the power of AI for contact centres — not just reducing workload, but fundamentally improving how organisations understand their customers.
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