What is it about?
Predicting customer engagement in the banking industry is crucial for customer satisfaction, loyalty, and bank profitability. Advanced technologies such as Explainable Ensemble Learning, Evidently AI, and Lime can be used to predict customer engagement accurately. A big set of data from a public source was used to organize and train four different prediction models, with the best one showing high accuracy. Using advanced AI methods can help banks predict customer engagement, leading to a better banking experience for all.
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Why is it important?
Customer engagement prediction is crucial in the banking industry as it affects various aspects of a bank's operations. Accurate predictions can enhance customer satisfaction, leading to loyalty, retention, and increased profitability. It also helps in resource allocation, risk management, and decision-making transparency. Effective prediction of customer engagement enables banks to provide personalized experiences and gain a competitive advantage.
Perspectives
Predicting customer engagement in the banking industry using accurate and transparent AI techniques can enhance the overall banking experience. Personalized service can make customers feel valued and understood, fostering trust and building lasting relationships. This can create a more customer-centric, efficient, and trustworthy banking industry.
Sudi Murindanyi
Makerere University
Read the Original
This page is a summary of: Explainable Ensemble Learning and Trustworthy Open AI for Customer Engagement Prediction in Retail Banking, August 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3607947.3607983.
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