fraud detection using a fuzzy expert system in motor insurance

Authors

سید محمد تقی تقوی فرد

دانشیار مدیریت صنعتی، دانشکدۀ مدیربت و حسابداری، دانشگاه علامه طباطبائی، تهران، ایران زهرا جعفری

کارشناس‎ارشد مدیریت فناوری اطلاعات، دانشکدۀ مدیربت و حسابداری دانشگاه علامه طباطبائی، تهران، ایران

abstract

insurance industry experts believe that fraud is a destructive disaster in the insurance industry. over the years, many methods have been used in the literature for fraud detection, one of which is expert systems. fraud detection expert systems are based on the knowledge of experts in the field of insurance identify fraud. judgment of experts is mostly based on evidence, documents, qualitative information which is often presented in verbal words to describe the fraudulent behavior. in the presented model, 61 qualitative and quantitative criteria related to the detection of fraud in car insurance were identified. then, these criteria were prioritized according to expert opinion and 17 criteria with the highest priority classified into eight factors were selected. in the suggested system fuzzy inference was performed using mamdani algorithm. finally, the designed system was implemented to an iranian private insurance company and the validity of the system assessed by a questionnaire and came up to 69.45%. the obtained results indicate that the proposed model is able to detect the fraud quite significantly.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

Fraud Detection in Health Insurance Using Expert Re-referencing

Fraud is widespread and very costly to the healthcare insurance system. Fraud involves intentional deception or misrepresentation intended to result in an unauthorized benefit. It is shocking because the incidence of health insurance fraud keeps increasing every year. In order to detect and avoid the fraud, data mining techniques are applied. Frauds blow a hole in the insurance industry. Health...

full text

PREDICTING URBAN TRIP GENERATION USING A FUZZY EXPERT SYSTEM

One of the most important stages in the urban transportation planning procedure is predicting the rate of trips generated by each trac zone. Currently, multiple linear regression models are frequently used as a prediction tool. This method predicts the number of trips produced from, or attracted to each trac zone according to the values of independent variables for that zone. One of the main li...

full text

ahp algorithm and un-supervised clustering in auto insurance fraud detection

this thesis is a study on insurance fraud in iran automobile insurance industry and explores the usage of expert linkage between un-supervised clustering and analytical hierarchy process(ahp), and renders the findings from applying these algorithms for automobile insurance claim fraud detection. the expert linkage determination objective function plan provides us with a way to determine whi...

15 صفحه اول

A Fuzzy Expert System & Neuro-Fuzzy System Using Soft Computing For Gestational Diabetes Mellitus Diagnosis

Gestational diabetes mellitus (GDM) is a kind of diabetes that requires persistent medical care in patient self management education to prevent acute complications. One of the common and main problems in diagnosis of the diabetes is the weakness in its initial stages of the illness. This paper intends to propose an expert system in order to diagnose the risk of GDM by using FIS model. The knowl...

full text

A Fuzzy Expert System & Neuro-Fuzzy System Using Soft Computing For Gestational Diabetes Mellitus Diagnosis

Gestational diabetes mellitus (GDM) is a kind of diabetes that requires persistent medical care in patient self management education to prevent acute complications. One of the common and main problems in diagnosis of the diabetes is the weakness in its initial stages of the illness. This paper intends to propose an expert system in order to diagnose the risk of GDM by using FIS model. The knowl...

full text

A Fuzzy Expert System for Predicting the Performance of Switched Reluctance Motor

In this paper a fuzzy expert system for predicting the performance of a switched reluctance motor has been developed. The design vector consists of design parameters, and output performance variables are efficiency and torque ripple. An accurate analysis program based on Improved Magnetic Equivalent Circuit (IMEC) method has been used to generate the input-output data. These input-output data i...

full text

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023