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Implementing a bank sales analytics solution and a predictive model for the next best offer
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| 2.85 MB | Adobe PDF |
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Orientador(es)
Resumo(s)
In the banking industry, the quantity of information that is processed is huge. Knowing also that clients are doted with changing needs every time, companies must adapt their approaches to attract clients with the best offers. That can be done by various machine learning and data mining techniques that enable them to understand better the clients. Also, internally, banks should be equipped with fast and efficient processes that enable them to take quickly the best decision. That is why real-time reporting tools should be implemented as an upper layer of the data sources. In this optic, this internship report is presenting 2 ambitious projects that aim to leverage Millennium BCP bank to a greater level in Analytics and Data Science. The first one is about building a Sales Analytics Solution to track weekly sales of retail products in the bank. The second one is about building a mechanism that will help reach to each client’s best adequate product to recommend.
Descrição
Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
Palavras-chave
Sales Marketing Campaign Recommendation System Reporting Next Best Offer Recommendation System