Using local outlier factor to detect fraudulent claims in auto insurance
عنوان مقاله: Using local outlier factor to detect fraudulent claims in auto insurance
شناسه ملی مقاله: JR_JMMF-2-1_009
منتشر شده در در سال 1401
شناسه ملی مقاله: JR_JMMF-2-1_009
منتشر شده در در سال 1401
مشخصات نویسندگان مقاله:
Maryam Esna-Ashari - Insurance Research Center, Tehran, Iran
Farzan Khamesian - Insurance Research Center, Tehran, Iran
Farbod Khanizadeh
خلاصه مقاله:
Maryam Esna-Ashari - Insurance Research Center, Tehran, Iran
Farzan Khamesian - Insurance Research Center, Tehran, Iran
Farbod Khanizadeh
Given the significant increase in fraudulent claims and the resulting financial losses, it is important to adopt a scientific approach to detect and prevent such cases. In fact, not equipping companies with an intelligent system to detect suspicious cases has led to the payment of such losses, which may in the short term lead to customer happiness but eventually will have negative financial consequences for both insurers and insured. Since data labeled fraud is really limited, this paper, provides insurance companies with an algorithm for identifying suspicious cases. This is obtained with the help of an unsupervised algorithm to detect anomalies in the data set. The use of this algorithm enables insurance companies to detect fraudulent patterns that are difficult to detect even for experienced experts. According to the outcomes, the frequency of financial losses, the time of and the type of incident are the most important factors to in detecting suspicious cases.
کلمات کلیدی: Unsupervised algorithm Fraud detection, Auto insurance, Classification
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1523433/