malpractice or opportunistic behavior of policyholders is one of the fundamental challenges of the insurance industry. Malpractice occurs when the insurance company's claim rate increases due to consumer behavior, in other words, the insurance company incurs more costs than expected. Malpractice increases costs, reduces efficiency, and disrupts market equilibrium. The present study aims to identify and analyze the impact of specific characteristics of insurance fields (such as contract design and risk assessment complexity) on malpractice in the Iranian insurance industry during the years 1376 to 1401. The research is of an applied and descriptive-analytical type. Decision tree and artificial neural network models were used to estimate malpractice, and the receiver operating characteristic curve was used to validate the results. In this study, it is assumed that specific characteristics of insurance fields can exacerbate behaviors leading to malpractice. To eliminate the scale effect of variables and to compare the regression coefficients of the claims data of fourteen insurance lines, they were standardized using Z-score. The findings showed that the fire and life insurance lines are most likely to cause malpractice due to their specific characteristics, such as the complexity of risk assessment and financial incentives. Validation of the results indicates the accuracy of the estimates and the high accuracy of the models used. Therefore, it is more necessary and recommended to improve professional ethics and risk management in these lines. Designing smart contracts, using digital claims assessment systems, and reviewing the tariff structure in a discipline-oriented manner should be on the agenda of insurance institutions and policymakers in these lines.