Leveraging Predictive Analytics to Personalize Financial Services and Payments

Authors: Abhijith Vijayakumar Binsu

DOI: https://doi.org/10.5281/zenodo.14565913

Short DOI: https://doi.org/g8w63h

Country: USA

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Abstract: This paper examines the role of predictive analytics in personalizing financial services and payments. By leveraging advanced machine learning algorithms and analyzing vast amounts of customer data, financial institutions can anticipate individual needs, deliver tailored offers, and optimize operations. The paper explores key applications such as customer segmentation, fraud detection, personalized product recommendations, and financial inclusion. It also addresses critical challenges, including data privacy concerns, algorithmic bias, and the integration of predictive models with legacy systems. Furthermore, the paper discusses emerging trends, such as the increasing use of alternative data sources and the advancements in artificial intelligence, that are shaping the future of personalized financial services. By addressing these critical aspects, this paper aims to provide valuable insights for stakeholders in the financial services industry, including financial institutions, policymakers, and technology providers, in their efforts to create a more customer-centric and inclusive financial ecosystem.

Keywords: Predictive Analytics Finance, AI in Finance, Personalized Finance, Financial Inclusion Analytics, Fraud Detection AI, Customer Segmentation Models, Fintech Analytics

Paper Id: 231929

Published On: 2021-07-06

Published In: Volume 9, Issue 4, July-August 2021

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