Studies reveal that only one in 26 customers share frustrations with an institution before they leave. This proves that in order for financial institutions to succeed in reducing customer attrition, they need to better anticipate and mitigate attrition risk, which can be done with an automated solution designed to proactively detect and analyze events and trends impacting customer satisfaction and dissatisfaction.
Aggregating data, including issue severity, timeframe, and impact on the overall relationship, enables FIs to calculate a predictive attrition risk score, quantifying the likelihood that a customer will leave the FI. When this score reaches a configurable threshold, appropriate and relevant customer engagement initiatives can be taken based on customer segmentation and preferences to remediate attrition risk.
Staff members should have the ability to view an individual customer’s predictive attrition risk score and engagement history on the customer profile. This helps the banker to determine best next steps to reduce attrition risk. At the enterprise level, this information helps provide management insight and reporting visualizations with drilldown capabilities for analyzation to identify and remediate organizational, regional, team, event, segment, and individual attrition causation and correlation.
With a solution in place that anticipates and mitigates attrition risk with a predictive expert model and proactive campaigns, FIs reduce losses, maintain high customer satisfaction, and protect the institution’s reputation.
Download ARGO’s Reducing Risk in the Omni-channel Delivery Environment interview brief.