Recommendation Systems in Banking and Finance Transforming Customer Experience and Operational Efficiency

Abstract

Modern organizations rely heavily on business intelligence and data analysis due to significant advancements in information technology. Organizations can optimize their business decisions by leveraging various computer technologies to better analyze their massive amounts of data. Recommendation system plays significant role and provides an optimized decision making to leverage the large amount of data. Various recommendation system is being discussed among the massive amount of data to deliver the quality data. Based on the discussion on the recommendation methodology related to real time applications, various challenges are listed, this pave the way to determine the scalability, sparsity and cold start problem. Recommendation system with an efficient technique being considered and various practical application examples are analyzed based on the business benefits. This helps to improve overall data quality and the efficacy of personalized recommendations for real time applications.