{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/5872"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/5872","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"A comparison of methods for modelling rates of withdrawal from insurance contracts","abstract":"Withdrawal from insurance contracts can be a significant risk for insurers. Withdrawal rates can be difficult to predict because withdrawal is influenced by a number of inter-related factors related to, inter alia, the sales process, characteristics of the insurance contract, characteristics of the contract holder, and economic variables. Existing methods used to model and predict withdrawal rates are initially reviewed. Two additional methods which have been proposed in the literature as means for modelling insurance risks are neural networks and Bayesian networks. These two methods are utilised in order to build models to compare their predictive ability with a commonly used method for modelling withdrawal rates, namely logistic regression.","abstract_html":"Withdrawal from insurance contracts can be a significant risk for insurers. Withdrawal rates can be difficult to predict because withdrawal is influenced by a number of inter-related factors related to, inter alia, the sales process, characteristics of the insurance contract, characteristics of the contract holder, and economic variables. Existing methods used to model and predict withdrawal rates are initially reviewed. Two additional methods which have been proposed in the literature as means for modelling insurance risks are neural networks and Bayesian networks. These two methods are utilised in order to build models to compare their predictive ability with a commonly used method for modelling withdrawal rates, namely logistic regression.","abstract_has_math":false,"creators":["Smith, Bradley"],"institution":"School of Management Studies","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["MacDonald, lain"],"committee_chairs":[],"committee_members":[],"year":2009,"date_issued":"2009","date_published":"2009","updated_at":"2026-07-22T22:23:24Z","subjects":[],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/5872","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["MacDonald, lain"]},{"key":"dc:creator","label":"Author","values":["Smith, Bradley"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-07-31T12:36:43Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-07-31T12:36:43Z"]},{"key":"dc:date.issued","label":"Date","values":["2009"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["School of Management Studies"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cape Town"]},{"key":"dc:type","label":"Dc Type","values":["Master Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Masters"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["MBusSc"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11427/5872"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Includes abstract.","Includes bibliographical references (p. 39-41)."]},{"key":"dc:description.abstract","label":"Abstract","values":["Withdrawal from insurance contracts can be a significant risk for insurers. Withdrawal rates can be difficult to predict because withdrawal is influenced by a number of inter-related factors related to, inter alia, the sales process, characteristics of the insurance contract, characteristics of the contract holder, and economic variables. Existing methods used to model and predict withdrawal rates are initially reviewed. Two additional methods which have been proposed in the literature as means for modelling insurance risks are neural networks and Bayesian networks. These two methods are utilised in order to build models to compare their predictive ability with a commonly used method for modelling withdrawal rates, namely logistic regression."]},{"key":"dc:title","label":"Title","values":["A comparison of methods for modelling rates of withdrawal from insurance contracts"]}]}],"canonical_facts":{"dc:contributor.advisor":["MacDonald, lain"],"dc:creator":["Smith, Bradley"],"dc:date.accessioned":["2014-07-31T12:36:43Z"],"dc:date.available":["2014-07-31T12:36:43Z"],"dc:date.issued":["2009"],"dc:description":["Includes abstract.","Includes bibliographical references (p. 39-41)."],"dc:description.abstract":["Withdrawal from insurance contracts can be a significant risk for insurers. Withdrawal rates can be difficult to predict because withdrawal is influenced by a number of inter-related factors related to, inter alia, the sales process, characteristics of the insurance contract, characteristics of the contract holder, and economic variables. Existing methods used to model and predict withdrawal rates are initially reviewed. Two additional methods which have been proposed in the literature as means for modelling insurance risks are neural networks and Bayesian networks. These two methods are utilised in order to build models to compare their predictive ability with a commonly used method for modelling withdrawal rates, namely logistic regression."],"dc:identifier.uri":["http://hdl.handle.net/11427/5872"],"dc:language.iso":["eng"],"dc:publisher.department":["School of Management Studies"],"dc:publisher.institution":["University of Cape Town"],"dc:title":["A comparison of methods for modelling rates of withdrawal from insurance contracts"],"dc:type":["Master Thesis"],"dc:type.qualificationlevel":["Masters"],"dc:type.qualificationname":["MBusSc"]},"updated_at":"2026-07-22T22:23:24Z"}