Corporate Transactions

The client, a commercial bank, faced significant challenges in analyzing the effectiveness of its sales agents. Traditional performance analysis methods relied heavily on supervisors listening to sampled calls and using surface-level metrics, which were often subjective and generic. This approach made it difficult to track agent performance comprehensively, leading to issues such as resentment among staff, lack of job satisfaction, and high turnover rates. To address these issues, EY implemented a tailored solution that utilized advanced machine learning and natural language processing (NLP) techniques. The goal was to create a system that provided greater visibility into agents' activities, including outreach, conversations, and follow-ups. EY's team curated a robust, fact-based comparative data set and analyzed conversation behaviors linked to successful outcomes. This analysis allowed the bank to develop a performance measurement and management framework that provided targeted coaching and quantified agent improvement over time. The results of this initiative were impressive. The bank experienced an uplift in opportunities of over 50%, thanks to the insights generated from the analysis of unstructured data from agent conversations. An interactive dashboard was created, offering agents and team leaders a comprehensive view of performance metrics and enabling personalized feedback. This data-driven approach eliminated bias in performance assessments and allowed for a recalibration of the incentive structure, ultimately leading to faster training and onboarding processes. Furthermore, the project enhanced the bank's ability to understand key drivers of effectiveness in a phone-based account development environment. It facilitated targeted coaching, improved product engagement, and increased upselling opportunities. The visibility gained from this initiative also allowed for better prioritization of account follow-ups and the potential automation of parts of the workflow, benefiting both the agents and their customers. Overall, the operationalization of these insights has the potential to be applied across various business functions, enhancing performance measurement and management in any environment reliant on phone-based interactions.