Automated Quality Management
Manual quality management processes are costly and ineffective.
First National Bank (FNB) is using Verint Quality Bot and advanced AI to discover what’s hidden in previously unmonitored interactions, reducing the risk of non-compliance and protecting the brand’s reputation.
Fourteen times more interactions evaluated in the sales department than with manual techniques only.
Fifteen percent more agents achieving an outstanding 90%+ quality score.
Evaluations can be used for employee coaching within one day – four times faster than manual scores
First National Bank (FNB) is using Verint Quality Bot and advanced AI to discover what’s hidden in previously unmonitored interactions, reducing the risk of non-compliance and protecting the brand’s reputation. By better understanding agent performance and service quality, South Africa’s oldest bank is already monitoring 14 times more sales interactions than previously. Moreover, 15% more advisors achieved 90%+ in their quality score in only three months.
First National Bank (FNB) provides personal, private, commercial, and corporate banking services to millions of customers across Africa. FNB is the oldest bank in South Africa and trades as a division of FirstRand Bank Limited.
The bank has been on a journey with Verint Speech Analytics and Verint Quality Management, providing actionable insights that improve the customer experience (CX). Some 38 business units comprising 6,400 users have already been onboarded to Verint, with more than 24 million calls analyzed last year.
However, quality management remained a manual process. Supervisors and quality teams spent hours manually listening to calls and grading them against scoring criteria – an expensive and time-consuming process.
Part of their role was to assess sales calls among the 1,400 advisors in the call center. South African financial compliance stipulates that certain phrases need to be referenced during the outbound client engagement, such as the advisor confirming they are calling from FNB and indicating that the calls are being recorded.
Until recently, FNB had many quality advisors (QAs) evaluating calls across the bank, performing approximately 45,000 manual evaluations per month. Yet, FNB had a limited monitoring capability as not all interactions were evaluated.
“Our goal was to automate more compliance checks, to improve quality, and reduce compliance risk. Automation would give us prompt, complete visibility into all performance and compliance issues.”
The Verint Quality Bot deployment was part of FNB’s forward-thinking engagement strategy to redefine every relevant customer interaction across the group and deliver great service every time. The Quality Bot uses AI to automate FNB’s quality evaluation process and discover what’s hidden among previously unmonitored interactions of the Sales, Outbound Service, Relationship Banking, and Collections teams.
Six questions are currently live. In Sales, for example, the bot explores whether the advisor read the “Calls Recorded” and FSP disclaimer verbatim. In Collections, it monitors questions such as did the advisor state that they were calling from FNB and that they needed to complete a security check.
With this move, more timely data is now available for compliance improvement. Interactions are automatically evaluated the same day, and results are available the next day for coaching. By contrast, QAs manually evaluated calls on average four days later.
Verint Quality Bot, powered by advanced AI, helps FNB automate their quality program and deliver real business outcomes now. By reviewing up to 100% of relevant interactions, the bank is improving service quality, CX, compliance, and employee performance.
Key benefits include:
“Make no mistake, Verint Quality Bot is making a huge difference to FNB’s compliance adherence. By monitoring significantly more interactions, we can turn our compliance strategy from reactive to proactive and assign training to reinforce proper compliance processes.”
Manual quality management processes are costly and ineffective.
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