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An intelligent method of predicting insurance claims fraud
Dissertation (MSc)--University of Pretoria, 2018.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2019
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| _version_ | 1867613613196312576 |
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| access_status_str | Open Access |
| author2 | Eloff, Jan H.P. |
| author_browse | Eloff, Jan H.P. |
| author_facet | Eloff, Jan H.P. |
| collection | Thesis |
| dc_rights_str_mv | © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Dissertation (MSc)--University of Pretoria, 2018. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/70994 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:38:55.836Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/70994 An intelligent method of predicting insurance claims fraud Eloff, Jan H.P. u16390572@tuks.co.za Kenyon, David Leicester UCTD Fraud prediction Machine learning Intelligent systems Claims fraud analysis Predictive analytics Insurance claims Engineering, built environment and information technology theses SDG-08 Engineering, built environment and information technology theses SDG-09 Engineering, built environment and information technology theses SDG-16 Dissertation (MSc)--University of Pretoria, 2018. Insurance fraud costs South Africa (and the global insurance industry) billions of Rands. Insurance claims fraud, which involves over-inflating claim amounts or fabricating a loss to result in a claim settlement, makes up a substantial portion of this cost. It would therefore be beneficial to the insurance industry to have a way of intelligently identifying insurance claims fraud. Current strategies focus on identifying fraud after the fact through methods such as auditing. These methods can be enhanced by predicting whether claims are fraudulent before they get paid, instead of after payment has already been made. Techniques in the fields of data science and machine learning can be used to intelligently predict insurance claims fraud, based on existing data. Because insurers have large sets of data, it is suggested that Big Data be factored in when predicting insurance claims fraud. However, new and proposed privacy legislation requires data scientists to be mindful and consider privacy when mining users’ personal information. The current research addresses the problems of insurance fraud, data bloat and information privacy by proposing a framework, model and architecture. The proposed framework contains the processes necessary to intelligently predict insurance claims fraud. The model that is suggested can be used to predict insurance claims fraud. The architecture shows software and hardware components that can be used to create a prototype. The research as a whole discusses this prototype, how it was developed, and how it was tested. bs2026 Computer Science MSc Unrestricted SDG-08: Decent work and economic growth SDG-09: Industry, innovation and infrastructure SDG-16: Peace, justice and strong institutions 2019-08-12T11:18:45Z 2019-08-12T11:18:45Z 2019/04/09 2018 Dissertation Kenyon, DL 2018, An intelligent method of predicting insurance claims fraud, MSc Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/70994> A2019 http://hdl.handle.net/2263/70994 en © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | UCTD Fraud prediction Machine learning Intelligent systems Claims fraud analysis Predictive analytics Insurance claims Engineering, built environment and information technology theses SDG-08 Engineering, built environment and information technology theses SDG-09 Engineering, built environment and information technology theses SDG-16 An intelligent method of predicting insurance claims fraud |
| title | An intelligent method of predicting insurance claims fraud |
| title_full | An intelligent method of predicting insurance claims fraud |
| title_fullStr | An intelligent method of predicting insurance claims fraud |
| title_full_unstemmed | An intelligent method of predicting insurance claims fraud |
| title_short | An intelligent method of predicting insurance claims fraud |
| title_sort | intelligent method of predicting insurance claims fraud |
| topic | UCTD Fraud prediction Machine learning Intelligent systems Claims fraud analysis Predictive analytics Insurance claims Engineering, built environment and information technology theses SDG-08 Engineering, built environment and information technology theses SDG-09 Engineering, built environment and information technology theses SDG-16 |
| url | http://hdl.handle.net/2263/70994 |