Reducing operating costs in banking using Rootlenses Voice AI

Executive Summary

Contact center operations in banking represent one of the most cost-intensive components of the traditional operating model. In markets with high digital competition and increasing regulatory pressure, financial margins are increasingly dependent on structural efficiency.

“Call centers also face complex staffing challenges, as schedules must adjust to call volume while simultaneously adapting to agent skills. The need for specialized knowledge in different product lines or customer segments adds complexity to workforce management,” explained IBM in an article on their website.

Contact centers not only generate direct costs in salaries and infrastructure; they also concentrate systemic inefficiencies: massive retries, low effective contact rate, variability in script adherence, human error in CRM updates, and regulatory exposure due to conversational inconsistencies.

According to a study cited by Hiring Branch and conducted by Call Center Helper, the average cost per call reached its highest level in five years in 2024.

And a study by Deloitte revealed that for every six contact centers, one now uses generative AI capabilities.

Traditional automation—based on rigid IVRs or bots with limited capabilities—has proven insufficient to structurally transform these costs. The new generation of enterprise Voice AI allows for redesigning operational execution from the architecture up.

Rootlenses Voice AI introduces an automated execution layer that:

• Reduces the cost per call.
• Optimizes retry logic.

Controls the conversational flow. Automatically synchronizes with CRM via programmable ETL. Improves traceability and regulatory auditability. Scales without a proportional increase in labor costs.

The goal is not to indiscriminately replace agents, but to transform the labor-intensive variable cost structure into a scalable, architecture-driven model.
 

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