Sökning: "Customer Prediction"

Visar resultat 1 - 5 av 110 uppsatser innehållade orden Customer Prediction.

1. 1. Explainable Artificial Intelligence and its Applications in Behavioural Credit Scoring

   Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Robert Iain Salter; [2023]
   Nyckelord :Behavioural Credit Scoring; Deep Learning; Machine Learning; Long Short-Term Memory; Default Prediction;

   Sammanfattning : Credit scoring is critical for banks to evaluate new loan applications and monitor existing customers. Machine learning has been extensively researched for this case; however, the adoption of machine learning methods is minimal in financial risk management. LÄS MER

3. 2. The sudden rise of neobanks and the threat it poses upon the traditional banking system.

   Kandidat-uppsats, Jönköping University/Internationella Handelshögskolan

   Författare :Victor Lindström; Olof Nilsson; [2023]
   Nyckelord :;

   Sammanfattning : The aim of this paper is to investigate the emergence of neobanks in the financial services industry, and whether they pose a threat to traditional banks. To successfully answer this, gaps in previous research and studies were examined to generate three research questions. LÄS MER

4. 3. Low-No code Platforms for Predictive Analytics

   Magister-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Författare :Soma Karmakar; [2023]
   Nyckelord :Low code; no code; Predictive analytics; databricks; azure; AWS; Google cloud;

   Sammanfattning : In the data-driven landscape of modern business, predictive analytics plays a pivotal role inanticipating and mitigating customer churn—a critical challenge for organizations. However, thetraditional complexities of machine learning hinder accessibility for decision-makers. LÄS MER

5. 4. Predicting user churn using temporal information : Early detection of churning users with machine learning using log-level data from a MedTech application

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Love Marcus; [2023]
   Nyckelord :User churn; Customer attrition; Artificial neural networks; Log-level analysis; Random forests; Decision trees; Användarbortfall; Kundbortfall; Artificiella neurala nätverk; logganalys; Slumpskogar; Beslutsträd;

   Sammanfattning : User retention is a critical aspect of any business or service. Churn is the continuous loss of active users. A low churn rate enables companies to focus more resources on providing better services in contrast to recruiting new users. LÄS MER

7. 5. Customer churn prediction in a slow fashion e-commerce context : An analysis of the effect of static data in customer churn prediction

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Luca Colasanti; [2023]
   Nyckelord :Survival Analysis; Time To Event prediction; Churn retention; Machine Learning; Deep Learning; Customer Clustering; E-commerce; Analisi di sopravvivenza; Previsione del tempo a evento; Ritenzione dall’abbandono dei clienti; Apprendimento automatico; Apprendimento profondo; Segmentazione della clientela; Commercio elettronico; Överlevnadsanalys; Tid till händelseförutsägelse; Churn Prediction; Maskininlärning; Djuplärning; Kundkluster; E-handel;

   Sammanfattning : Survival analysis is a subfield of statistics where the goal is to analyse and model the data where the outcome is the time until the occurrence of an event of interest. Because of the intrinsic temporal nature of the analysis, the employment of more recently developed sequential models (Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM)) has been paired with the use of dynamic temporal features, in contrast with the past reliance on static ones. LÄS MER