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Found 5 essays matching the above criteria.

  1. 1. Using Gradient Boosting to Identify Pricing Errors in GLM-Based Tariffs for Non-life Insurance

    University essay from KTH/Matematik (Avd.)

    Author : Felix Greberg; Andreas Rylander; [2022]
    Keywords : GLM; Gradient Boosting; XGBoost; Non-life insurance; Property Casualty; Rate making; Insurance Tariff; MTPL insurance; Machine learning; Regression trees; Tweedie regression; Credit risk; GLM; Gradient Boosting; XGBoost; Skadeförsäkring; Prissättning; Försäkringstariff; Trafikförsäkring; Regressionsträd; Maskininlärning; Tweedie-regression; Kreditrisk;

    Abstract : Most non-life insurers and many creditors use regressions, more specifically Generalized Linear Models (GLM), to price their liabilities. One limitation with GLMs is that interactions between predictors are handled manually, which makes finding interactions a tedious and time-consuming task. READ MORE

  3. 2. Increasing Retention in Insurtechs Through Churn Prediction

    University essay from Lunds universitet/Innovationsteknik

    Author : John Rapp Farnes; Oskar Christiansen; [2021]
    Keywords : Non-life insurance; Property and casualty insurance; Customer retention; Churn prediction; Predictive analytics; Classification; Machine learning; Mathematics and Statistics;

    Abstract : Over the last decades, the Swedish insurance industry has seen decreased entry barriers due to deregulation and emerging new technologies, which have the potential to disturb the stagnated and consolidated competitive landscape of the industry. Initiated by newcomers like American insurance startup Lemonade, and later Swedish Hedvig among others, there is an increased push toward digitalization, transparency, and automation in the industry. READ MORE

  4. 3. Risk Premium Prediction of Car Damage Insurance using Artificial Neural Networks and Generalized Linear Models

    University essay from KTH/Matematisk statistik

    Author : Lovisa Styrud; [2017]
    Keywords : ;

    Abstract : Over the last few years the interest in statistical learning methods, in particular artificial neural networks, has reawakened due to increasing computing capacity, available data and a strive towards automatization of different tasks. Artificial neural networks have numerous applications, why they appear in various contexts. READ MORE

  5. 4. Predicting customer level risk patterns in non-life insurance

    University essay from KTH/Matematisk statistik

    Author : Erik Villaume; [2012]
    Keywords : Predictive Modeling; Generalized Linear Models; Artificial Neural Networks.;

    Abstract : Several models for predicting future customer profitability early into customer life-cycles in the property and casualty business are constructed and studied. The objective is to model risk at a customer level with input data available early into a private consumer’s lifespan. READ MORE

  6. 5. Managing Customer Loyalty through Direct Marketing : A Case Study of the Relationship between Länsförsäkringar Kalmar Län And Their Beneficiary Customers

    University essay from IHH, EMM (Entrepreneurskap, Marknadsföring, Management)

    Author : Angelica Andersson; Petter Cederbrink; Magnus Lövsund; [2009]
    Keywords : Customer Loyalty; Direct Marketing; Relationship Marketing; CRM; Kundlojalitet; Direkt marknadsföring; Relationsmarknadsföring; CRM;

    Abstract : Background: LF is active in three markets: Property & casualty insurance, pension and banking. The main objective for such a strategy is to differentiate by offering all the services to the customer who can enjoy the benefits of having their whole personal economy at one place. READ MORE