About
FE CREDIT is currently a leading financial company with over 12 million customers. In order to serve this vast customer base, FE CREDIT has invested in a state-of-the-art call center ecosystem, the largest in Southeast Asia. This investment serves as a foundation for FE CREDIT’s ambition to dominate the consumer finance market.
Challenges
FE Credit is currently facing significant operational challenges in its call center, primarily stemming from the management of over 1 million daily calls. These challenges include assessing the proficiency of call center agents, implementing effective training programs, and establishing performance incentives with measurable outcomes. Additionally, FE Credit seeks to optimize cost savings while effectively managing fraud risks associated with its operations. To address these multifaceted challenges, FE Credit has recognized the potential of Voicebot AI technology, aiming to automate outbound calling processes, enhance call quality assessment, and bolster fraud detection capabilities.
Solution
FE Credit can optimize resources and costs by utilizing Voicebot Virtual Agent as a “Super Call Center Agent” to perform tasks such as telesales for loan products, payment reminder calls, and customer support. Instead of hiring additional call center agents, Voicebot Virtual Agent can automate these processes, helping FE Credit save costs and enhance customer service efficiency.
Assessing the performance of call center agents, and subsequently providing evidence for rewards or penalties, becomes easier with the use of the Call Evaluation solution – Virtual QC. By analyzing call data and audio, Virtual QC can identify specific criteria set by the business and analyze the emotions of both employees and customers during communication. This helps FE Credit save evaluation time and significantly reduce operational costs.
Virtual Agent
Over an 11-month period, the Virtual Agent successfully managed an impressive total of 1,054,670 calls, demonstrating its capability to handle high call volumes efficiently. During peak hours, an average of 52,152 calls per day were processed, ensuring uninterrupted customer service even during periods of intense activity. Notably, the Virtual Agent exhibited outstanding accuracy in identifying customer intent, achieving an impressive range of 85% to 92%.
Virtual QC
With an analysis accuracy rate of up to 85%, it provided valuable insights into call quality and agent performance. Moreover, the system demonstrated an 80.7% success rate in recognizing employee attitude keywords, facilitating effective monitoring and improvement of customer service interactions.