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Insurance claim risk scoring with machine learning algorithms: A case study on developing a predictive system for assessing corporate customers' claim risk
(2018)
Predictive learning algorithms offer tools to automate and improve insurance risk management. The aim of this thesis is to study classification algorithms in risk scoring applications and to evaluate them in the creation ...
Tekoälyn ja koneoppimisen liiketoimintamahdollisuudet teollisuusyrityksessä
(2018)
Tässä kandidaatintyössä selvitetään, miten tekoälyn malleilla luodaan arvoa yritykseen. Työn lopussa esitetään ehdotus tekoälyn potentiaalisista sovelluskohteista kohdeyrityksen prosesseissa. Työssä hyödynnetään aiheeseen ...
Segmentation of investor customers using machine learning in banking
(2021)
The purpose of this study is to analyze customer data from a local retail bank using machine learning. The goal is to detect attributes that investment customers have. Furthermore, this study compares performances of ...
Real estate insurance claims prediction with machine learning algorithms
(2022)
Nowadays insurance companies are increasingly implementing machine learning algorithms in their business routine. An ability to determine beforehand an emergence of claims could offer a tool to increase a profitability of ...
Predicting lead times of purchase orders using gradient boosting machine
(2020)
A company can make more accurate predictions of its internal processes and sales lead
times when it has accurate predictions of the lead times of purchase orders. It results in more
efficient processes as well as improved ...
Machine learning in predictive maintenance : classification approach for remaining useful life prediction
(2020)
This thesis focuses on predicting remaining useful life (RUL) with classification approach. The methodology is demonstrated with NASA’s turbofan engine degradation dataset. Three classification systems with different ...
Utilizing machine learning in data-driven pricing
(2020)
The rapidly increasing volume and variety of data and the continuous development of the technologies used for data processing have enabled the use of dynamic data-driven pricing. While pricing can be considered as one of ...
Modelling customer churn with private electricity customer data
(2021)
The objective of this thesis is to study customer churn problem in a Finnish electricity company. First, the theory of customer churn, logistic regression, and decision tree methodology is studied and then that information ...
Forecasting stock index trend with Support Vector Machine and Long- Short term memory : a case study of models fitted on OMXH25 data
(2021)
The aim of this thesis is to investigate the predictability of financial markets. The research is conducted by using machine learning and deep learning techniques to predict the next day’s direction of the stock index ...
Predicting churn using machine learning methods : case study for SaaS company
(2022)
In this thesis, the objective was to study customer churn prediction as a case study for a private company. First, the previous literature was reviewed to understand what type of methods were used previously that had brought ...