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Inshore Insurance ltd. is a regulated financial institution whose head office is situated in Sydney. The general and accidental insurance services are provided by the company. The in-house activities of the company are managed by deploying the IT service. The cloud services are incorporated in the working curriculum of the business.
The problem is to diagnose the time and location which are associated with the crimes and accident to claim for the insurance cost associated with personal, household, and vehicular claims. The company is looking forward for developing the IT solution for predicting the time and location of the crime.
The use of ICT technology in the fraud detection for the insurance company helps in analysing the cause of the victim to claim for the insurance money. “The high level analysis can be effectively done with the ICT information system” (Pandhare, 2014). The cloud platform is deployed within the working curriculum of the organization to know the real cause of claim.
The cloud services helps in developing relationship with different actors to bring transparency, liability, and responsibility in the current working culture. The main purpose of this project is to analyse how cloud services works in different situation.
The constraints related with the data sensitivity and threat model are reliability, security, availability, cost, complexity, performance, and legal issues migration, performance, lack of standards, reversion, lack of customization, and privacy issues.The new system is designed to exclude the flaws of the traditional working system. The new system is relevant for excluding the cost and time wasted in performing the investigation program for knowing the reason of claim.
“The deployment of the cloud services helps in raising the satisfaction of the customers by making use of behavioural analytics and biometrics for the identification of unauthorised access” (Yang, 2013). The working system can adapt its intelligence with the evolution of the threats. The operational efficiency of the system can be improved with the use of cloud based services by reducing the time and cost spent on the detection and investigation program for insurance claims.The following diagram shows the working architecture of the cloud based services in the Inshore Insurance ltd.
The project governance process aligns the risks associated with the threat model by providing security to the computing environment and policies, managing the implementation of the cloud services, management of the demand and supply, management of the relationship between different actors, and managing the application services.
The role of the actor should be identified in terms of data controller, data processor, and data subject.
In the proposed architecture:
The system interface should have the following features:
“The responsibility, transparency, and liability are the major constraints associated with the deployment of the cloud conceptual framework” (Barret, 2013).The following diagram shows the interface of the sub-system:
The focus should be given on managing the personal and sensitive data. The performance can be measured with the management of large volume of data stored in the database.
The design should focus on the user, distribution of report, prediction of location and incident occurred, and periodically updating of security architecture.
The testing of the system can be done by focusing on the security system which is used for overcoming the risks associated with the system.
Barret, S. (2013). Insurance fraud and abuse: A very serious problem. 1st ed. [ebook]. https://www.quackwatch.org/02ConsumerProtection/insfraud.html [Accessed 10 Sep. 2017].
Dora, P. (2013). Insurance fraud detection leveraging big data analytics. 1st ed. [ebook]. https://www.ijsr.net/archive/v4i4/SUB153497.pdf [Accessed 10 Sep. 2017].
Hargreaves, C. (2016). Analytics for insurance fraud detection: Na empirical study. 1st ed. [ebook]. https://www.researchgate.net/publication/291833022_Analytics_for_Insurance_Fraud_Detection_An_Empirical_Study [Accessed 10 Sep. 2017].
Joudaki, H. (2013). Using data mining to detect health care fraud and abuse: A literature review. 1st ed. [ebook]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4796421/ [Accessed 10 Sep. 2017].
Kirlidog, M. (2016). A fraud detection approach with data mining in health. 1st ed. [ebook]. http://www.sciencedirect.com/science/article/pii/S1877042812036099 [Accessed 10 Sep. 2017].
Morley, N. (2016). How the detection of insurance fraud succeeds and fails. 1st ed. [ebook]. http://eprints.lancs.ac.uk/974/2/PsyCrime&Law_06.pdf [Accessed 10 Sep. 2017].
Pandhare, S. (2014). Big data analytics: New Whistleblower on insurance fraud. 1st ed. [ebook]. https://www.infosys.com/industries/insurance/white-papers/Documents/new-whistleblower-insurance-fraud.pdf [Accessed 10 Sep. 2017].
Yang, G. (2013). Using advanced analytics to combat claim and fraud. 1st ed. [ebook]. https://www.cognizant.com/InsightsWhitepapers/Using-Advanced-Analytics-to-Combat-PandC-Claims-Fraud.pdf [Accessed 10 Sep. 2017].
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