Publicação
Data analytics in the private banking industry : a case study at Banco Carregosa
| Resumo: | The Private Banking sector in Portugal has been evolving with the current technological developments. At this segment of national banking industry, Banco Carregosa excels in the relationship with its customers, supported by the personalized treatment and customized offer so that each customer is supplied with a variety of products and services that meet their values and the ones shared by the Bank. This happens by considering all the information the Bank has about the customer, coming from a wide range of data sources. In this Master Final Assignment we wanted to deepen the knowledge about the client and the Bank's products by performing analysis conducted through Machine Learning techniques such as Clustering, Market Basket Analysis and study of the churners. In addition to this, we developed dashboards containing relevant information about customers, accounts, leads and their conversions into accounts, bank products and movements in the capital markets, all geared to better understand the customer's next step and also equip Banco Carregosa with valuable information for decision making, having it available in a quick, intuitive and explanatory way. This way, we use a variety of techniques, namely, K-means, Apriori algorithm, Naïve Bayes, Logistic Regression and Dashboards. In the end, we concluded that the use of Business Intelligence, Analytics and Data Mining can feed good, precise and valuable information to Banco Carregosa. It also allows key decision makers in the organization to know more about how’s the Bank performing, the clients and support their everyday decisions with analytics and quantifiable information, available at a glance. |
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| Autores principais: | Costa, André Macedo da |
| Assunto: | Private banking Business intelligence Business analytics Data mining Dashboards KYC |
| Ano: | 2021 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Universidade Católica Portuguesa |
| Idioma: | inglês |
| Origem: | Veritati - Repositório Institucional da Universidade Católica Portuguesa |
| Resumo: | The Private Banking sector in Portugal has been evolving with the current technological developments. At this segment of national banking industry, Banco Carregosa excels in the relationship with its customers, supported by the personalized treatment and customized offer so that each customer is supplied with a variety of products and services that meet their values and the ones shared by the Bank. This happens by considering all the information the Bank has about the customer, coming from a wide range of data sources. In this Master Final Assignment we wanted to deepen the knowledge about the client and the Bank's products by performing analysis conducted through Machine Learning techniques such as Clustering, Market Basket Analysis and study of the churners. In addition to this, we developed dashboards containing relevant information about customers, accounts, leads and their conversions into accounts, bank products and movements in the capital markets, all geared to better understand the customer's next step and also equip Banco Carregosa with valuable information for decision making, having it available in a quick, intuitive and explanatory way. This way, we use a variety of techniques, namely, K-means, Apriori algorithm, Naïve Bayes, Logistic Regression and Dashboards. In the end, we concluded that the use of Business Intelligence, Analytics and Data Mining can feed good, precise and valuable information to Banco Carregosa. It also allows key decision makers in the organization to know more about how’s the Bank performing, the clients and support their everyday decisions with analytics and quantifiable information, available at a glance. |
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