A Monte Carlo Simulation to The Fraud Information of Investment Scams in Taiwan

A Monte Carlo Simulation to The Fraud Information of Investment Scams in Taiwan

Fraud has been a significant form of crime since ancient times, involving various types of fraudulent activities. Based on the incident data published on the 165 anti-fraud platform in Taiwan for the period from January 2022 to April 2023, the number of“investment scams”accounted for 20.88% of all cases, ranking first among the 43 types of fraud. The second most common type of fraud was“cancellation of installment fraud,”accounting for 16.29%, followed by“fake online auctions”at 13.79%. Investment scam cases always result in significant financial losses for each individual involved, with 91.52% of these cases being perpetrated through the internet. Government departments develop countermeasures by categorizing fraud cases based on factors such as fraud methods, information and communication channels, and financial flow analyses. This helps quantify financial losses and propose prevention measures. Researchers primarily propose prevention frameworks or fraud models to detect and prevent specific types of fraudulent activities. However, there has been a lack of scientific evaluation of the effectiveness of the countermeasures proposed by governments or researchers. This is mainly because of the difficulties in assessing and predicting the number of cases and financial losses. This paper introduces a regression analysis to investigate the correlation between the frequency of investment scam cases and the corresponding financial losses. Furthermore, Monte Carlo simulation is used to estimate the frequency of investment scams on a monthly basis. The effectiveness of domain name redirection as a countermeasure is simulated and examined, considering the configuration and operation of internet domain name settings. The simulation tests indicate that this preventive method has the potential to decrease financial losses by approximately 3.4% to 7.5% per month.