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Visar resultat 1 - 5 av 31 uppsatser som matchar ovanstående sökkriterier.

1. 1. A Predictive Analysis of Customer Churn

   Kandidat-uppsats, KTH/Matematisk statistik

   Författare :Olivia Eskils; Anna Backman; [2023]
   Nyckelord :Churn prediction; CRM; optimization; applied mathematics; machine learning; gradient boosting; random forest; logistic regression; insurance industry; Kundbortfall; CRM; optimering; tillämpad matematik; maskininlärning; gradient boosting; random forest; logistisk regression; försäkringsbranschen;

   Sammanfattning : Churn refers to the discontinuation of a contract; consequently, customer churn occurs when existing customers stop being customers. Predicting customer churn is a challenging task in customer retention, but with the advancements made in the field of artificial intelligence and machine learning, the feasibility to predict customer churn has increased. LÄS MER

3. 2. Predicting Risk Level in Life Insurance Application : Comparing Accuracy of Logistic Regression, DecisionTree, Random Forest and Linear Support VectorClassifiers

   Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Pulagam Karthik Reddy; Sutapalli Veerababu; [2023]
   Nyckelord :Decision Tree Classifier; Logistic Regression; Machine Learning; Random Forest Classifier; Linear Support Vector Classifier;

   Sammanfattning : Background: Over the last decade, there has been a significant rise in the life insurance industry. Every life insurance application is associated with some level ofrisk, which determines the premium they charge. The process of evaluating this levelof risk for a life insurance application is time-consuming. LÄS MER

4. 3. Deep Learning-Based Approach for Fusing Satellite Imagery and Historical Data for Advanced Traffic Accident Severity

   Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Gowtham Kumar Sandaka; Praveen Kumar Madhamsetty; [2023]
   Nyckelord :Traffic accidents; Satellite imagery; Logistic Regression; Random Forest; SVC; VGG19; hybrid model; CNN; self-driving cars; best-performing algorithm; literature review;

   Sammanfattning : Background. This research centers on tackling the serious global problem of trafficaccidents. With more than a million deaths each year and numerous injuries, it’svital to predict and prevent these accidents. LÄS MER

5. 4. Exploring the Dynamics of Damage Costs Inflation on Insurance Matters : An In-depth Regression Analysis on Macroeconomic Variables

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Jacob Liljestrand; Fredrik Nyberg; [2023]
   Nyckelord :Inflation; Time lag; Regression; Macroeconomic variables; Insurance;

   Sammanfattning : The aim of this thesis consist of three parts. Firstly, the aim was to developan accurate historical inflation index suitable for the insurance business, usinginformation about insurance matters. The calculated inflation index was compared to an in-house benchmark at the insurance company Gjensidige, it wasfound to be a good match. LÄS MER

7. 5. Customer Acquisition Process Digitalization: A Case Study on the Use of Machine Learning in The Corporate Insurance Industry

   Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

   Författare :Klara Larsson; Freja Ling; [2023]
   Nyckelord :Customer Relationship Management CRM ; Customer Classification; Customer Acquisition; Machine Learning; Insurance Industry; Corporate Insurance; B2B; AI-CRM; Kundrelationssystem CRM ; Kunklassificering; Nykundsbearbetning; Maskininlärning; Försäkringsbranchen; Företagsförsäkring; B2B; AI-CRM;

   Sammanfattning : This thesis explores the application of machine learning 8ml9 techniques in customer classification and their intergration into customer relationship management (CRM) systems within the corporate insurance industry. The research aims to address the gap in the use of AI-CRM for the corporate insurance industry. LÄS MER