Managing customer complaints is one of the most important activities for a financial institution. Approximately 40% of financial consumers cited complaints management as a key factor in determining the extent to which they trust their financial institution. And failure to manage complaints can result in large penalties. Between April and June 2018 alone, the Consumer Financial Protection Bureau (CFPB) issued $1.3 billion in fines to banks related to complaints management.
Complaints management is often reactive rather than proactive. However, Synechron has leveraged its latest AI accelerator to empower banks to fully automate and proactively manage customer complaints. Synechron’s accelerator applies natural language processing to complaint narratives and Random Forest Models to complaint features to predict complaints likely to be disputed. The Accelerator’s machine learning models identify the factors driving customer complaints and provide a detailed list of complaints prioritized by the likelihood of being disputed or escalated. Currently integrated with the CFPB’s data API to extract complaints on an ongoing, real-time basis, Synechron’s accelerator can sit on top of proprietary CRM platforms or other sources of consumer complaints data. Using publicly available data, the accelerator currently predicts complaint resolution with 80-85% accuracy and continuously learns from new complaints to improve accuracy over time. The result is a fully automated accelerator that enables banks to proactively resolve the most critical complaints in a fully automated fashion while significantly reducing the time required to process and react to thousands of complaints filed with the CFPB.