Please use this identifier to cite or link to this item: http://hdl.handle.net/10362/165797
Title: AI-driven Customer Analytics: Implementation of Machine Learning Solutions into bank’s CRM
Author: Trzos, Julia Marianna
Advisor: Neto, Miguel de Castro Simões Ferreira
Jardim, João Bruno Morais de Sousa
Keywords: Business Intelligence
Machine Learning
Banking
Customer Relationship Management
Artificial Intelligence
Customer Segmentation
Defense Date: 31-Jan-2024
Abstract: In the ever-evolving landscape of modern banking, the incorporation of emerging technologies, specifically Artificial Intelligence and machine learning, holds great significance in order to remain relevant and efficiently address customer needs, having a potential for significant enhancements in customer relationship management practises within the banking industry. The objective of this project, conducted in collaboration with the Asseco PST Data & Analytics team, is to improve their CRM solution by incorporating a comprehensive machine learning framework. This involves utilising machine learning techniques to segment clients, with the goal of optimising customer relationship management (CRM) and providing data-driven campaigns for their bank clients. The project aims to develop a clustering-based Recommendation System that delivers customised product recommendations. Furthermore, the project presents a deployment demonstration involving the creation of apps aimed at achieving a scalable solution for clustering and predictive modelling, hence facilitating the implementation process for new clients. Additionally, this project intends to establish itself as an important component within Asseco PST's comprehensive offering. The integration of this work within their pre-existing CRM development offer serves to underscore its importance and possible influence within the constantly developing world of present-day banking.
Description: Internship Report presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Digital Marketing and Analytics
URI: http://hdl.handle.net/10362/165797
Designation: Mestrado em Marketing Analítico, especialização em Marketing Digital e Análise de Dados
Appears in Collections:NIMS - Dissertações de Mestrado em Marketing Analítico (Data-Driven Marketing)

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