Operations Research on Customer Complaints in Fintech using ARIMA & Holt-Winters Method and LSTM (Long Short-Term Memory Networks)

Operations Research on Customer Complaints in Fintech using ARIMA & Holt-Winters Method and LSTM (Long Short-Term Memory Networks)

Report

Operations Research on Customer Complaints in Fintech using ARIMA & Holt-Winters Method and LSTM (Long Short-Term Memory Networks)

This paper aims to analyse and forecast customer complaints for the fintech industry based on ARIMA, Holt-Winters, and Long Short-Term Memory (LSTM) networks. Given the rise of the use of digital financial services, prediction of complaints enables firms to improve customer relations and system performance.

  • Use cases, geography and tags
  • Organizations that created, adopted or are mentioned
  • Ecosystem position
  • Link to the original asset
  • Comments and reactions