Detecting Smartphone Insurance Fraud
(2019) INTM01 20191Innovation Engineering
- Abstract
- The vast majority of Swedes are in possession of a smartphone, typically covered via one’s household insurance policy and smartphones are included in upwards of 50 % of household insurance claims (Hedvig, 2019). Some estimates say that upwards of 40 % of all smartphone claims are fraudulent. Payments to fraudsters falls on honest policy holders pay for with higher premiums. There are several vulnerabilities in the current measures of Insurance Fraud Detection (IFD) on smartphones regarding the indicators that invoke suspicion and the economic incentives for investigation. The purpose of this report was to identify viable Smartphone Insurance Fraud Indicators (SIFIs) to be used for IFD, along with suggestions for further improving the fraud... (More)
- The vast majority of Swedes are in possession of a smartphone, typically covered via one’s household insurance policy and smartphones are included in upwards of 50 % of household insurance claims (Hedvig, 2019). Some estimates say that upwards of 40 % of all smartphone claims are fraudulent. Payments to fraudsters falls on honest policy holders pay for with higher premiums. There are several vulnerabilities in the current measures of Insurance Fraud Detection (IFD) on smartphones regarding the indicators that invoke suspicion and the economic incentives for investigation. The purpose of this report was to identify viable Smartphone Insurance Fraud Indicators (SIFIs) to be used for IFD, along with suggestions for further improving the fraud detection capability in areas of data acquisition and investments in analytical tools. A triangulation methodology was employed, which extended to interviews with 12 practitioners of IFD, attendance at 2 international insurance conferences and a review of 20 published academic papers and articles on insurance fraud. The primary result of this report was a compilation of 51 distinct SIFIs. By contrasting and comparing the findings from the three method areas, several examples of divergences between theory and practice were identified. The results can be used to expand and revise existing sets of indicators, as well as prioritising investments in new analytical tools. Although the research is focused on smartphone claims, the results also have the potential to be apply to other common belongings such as laptops, and tablets. (Less)
- Popular Abstract (Swedish)
- De flesta svenskar äger en smartphone, en ägodel som normalt täcks via hemförsäkring. Smartphones ingår i uppemot 50 % av alla skador som rapporteras till försäkringsbolaget Hedvig (Hedvig, 2019). Vissa experter rapporterar att så mycket som 40 % av alla smartphoneärenden som anmäls till försäkringsbolagen är bedrägliga. Den ersättning som betalas ut till bedragarna subventioneras via övriga försäkringstagares premier. Det finns flera sårbarheter i den nuvarande utredningsmetodiken som syftar till att identifiera bedrägliga försäkringsärenden (IFD) som rör smartphones gällande indikationerna som väcker misstänksamhet och de ekonomiska incitamenten för att initiera en utredning. Syftet med denna rapport var att identifiera användbara... (More)
- De flesta svenskar äger en smartphone, en ägodel som normalt täcks via hemförsäkring. Smartphones ingår i uppemot 50 % av alla skador som rapporteras till försäkringsbolaget Hedvig (Hedvig, 2019). Vissa experter rapporterar att så mycket som 40 % av alla smartphoneärenden som anmäls till försäkringsbolagen är bedrägliga. Den ersättning som betalas ut till bedragarna subventioneras via övriga försäkringstagares premier. Det finns flera sårbarheter i den nuvarande utredningsmetodiken som syftar till att identifiera bedrägliga försäkringsärenden (IFD) som rör smartphones gällande indikationerna som väcker misstänksamhet och de ekonomiska incitamenten för att initiera en utredning. Syftet med denna rapport var att identifiera användbara indikatorer för smartphonebedrägerier (SIFIs), samt att föreslå ytterligare förbättringar inom IFD på områden som datainsamling och investeringar i analytiska verktyg. En trianguleringsmetodik användes som inbegrep intervjuer med 12 praktiserare av IFD, deltagande på 2 internationella försäkringskonferenser och en literaturgenomgång av 20 stycken publicerade akademiska artiklar om försäkringsbedrägeri. Det primära resultatet av arbetet var en sammanställning av 51 olika SIFIs. Genom att kontrastera och jämföra resultaten från de tre undersökningsområdena kunde flera exempel på divergens mellan teori och praktik identifieras. Resultatet kan användas för att utöka och omvärdera befintliga uppsättningar av indikatorer och prioritera investeringar i nya analytiska verktyg. Denna rapport fokuserar på smartphoneskador, men delar av resultatet är potentiellt applicerbart även på andra vanliga tillhörigheter såsom datorer och läsplattor. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8988906
- author
- Angtoft, Björn LU and Hallqvist, Olof LU
- supervisor
-
- Emil Åkesson LU
- organization
- course
- INTM01 20191
- year
- 2019
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- insurance, insurance fraud, insurance fraud detection, smartphone, insurance fraud indicators
- language
- English
- id
- 8988906
- date added to LUP
- 2019-06-29 16:43:07
- date last changed
- 2019-06-29 16:43:07
@misc{8988906,
abstract = {{The vast majority of Swedes are in possession of a smartphone, typically covered via one’s household insurance policy and smartphones are included in upwards of 50 % of household insurance claims (Hedvig, 2019). Some estimates say that upwards of 40 % of all smartphone claims are fraudulent. Payments to fraudsters falls on honest policy holders pay for with higher premiums. There are several vulnerabilities in the current measures of Insurance Fraud Detection (IFD) on smartphones regarding the indicators that invoke suspicion and the economic incentives for investigation. The purpose of this report was to identify viable Smartphone Insurance Fraud Indicators (SIFIs) to be used for IFD, along with suggestions for further improving the fraud detection capability in areas of data acquisition and investments in analytical tools. A triangulation methodology was employed, which extended to interviews with 12 practitioners of IFD, attendance at 2 international insurance conferences and a review of 20 published academic papers and articles on insurance fraud. The primary result of this report was a compilation of 51 distinct SIFIs. By contrasting and comparing the findings from the three method areas, several examples of divergences between theory and practice were identified. The results can be used to expand and revise existing sets of indicators, as well as prioritising investments in new analytical tools. Although the research is focused on smartphone claims, the results also have the potential to be apply to other common belongings such as laptops, and tablets.}},
author = {{Angtoft, Björn and Hallqvist, Olof}},
language = {{eng}},
note = {{Student Paper}},
title = {{Detecting Smartphone Insurance Fraud}},
year = {{2019}},
}