Forecasting financial services of a call center’s inbound volumes : A case study - Shamsuzzoha, Ahm; Viitanen, Joonas; Piya, Sujan; Khadem, Mohammad; Shamsuzzaman, Mohammad (Sage, 2025)
The objective of this study is to build a predictive model for the call center of a financial services company using predictive analytics methods. Using this model, the organization would be able to transition from a reactive approach to operational resource allocation to a more proactive one in handling inbound calls. This study uses a quantitative methodology, as it provides a structured, objective, and rigorous framework essential for developing, testing, and validating forecasting models. Quantitative methods’ reliance on numerical data and statistical techniques ensures accuracy, reliability, and the ability to generalize findings. This study contributes valuable insights into the application of time series forecasting models in optimizing resource allocation and enhancing service quality within the call centres, particularly within the financial services industry. By addressing the identified research gap and providing practical recommendations, this research offers an addition to further advancements in call center forecasting methodologies, facilitating more efficient and effective operations within financial organizations.
Keywords: call centre; time series forecasting; financial service; resource allocation; autoregressive integrated moving average (ARIMA) model; fi=Tuotantotalous|en=Industrial Management|