Early Detection of Insurance Fraud through Social Networks

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Summary

The proposed early detection of insurance fraud model uses a multi-disciplinary approach consisting of Context, Actor’s Role, and Semantics (CRS). This will involve representation and simulation of the user’s environment, risk identification, assessment, and mitigation.

Supervisor(s)

Professor Liaquat Hossain

Research Location

Civil Engineering

Program Type

N/A

Synopsis

It is proposed to simulation the CRS approach to evaluate early detection of insurance fraud models which exhibit both organizational and social structure, insurance claims behaviour, and risk-generating events. The proposed approach offers a unique opportunity to combine socio-technical, information security and natural language processing, with in a relevant insurance community fraud detection scenario. It is intended to develop and deploy a prototype which can be used to capture insurance claims behaviour monitor events and detect fraud-related/abnormal activity.

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Keywords

insurance, fraud, insurance fraud, social networks, Early Detection, early detection of insurance fraught, multi-disciplinary approach, Context, Actor’s Role, and Semantics, CRS, fraud detection

Opportunity ID

The opportunity ID for this research opportunity is: 809

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