Objectives: Tourism has become one of the main economic sectors of the 21st century. Today, tourism is facing various security threats such as terrorism, crime and potential armed conflicts, and the most common security threat to tourism is crime. The aim of this paper is to analyse how crime affects security in tourism and to describe the consequences of crime for tourism. Methods: A descriptive method was used in this paper to explain the concept of security in tourism and to analyse the relationship between tourism and crime. The data was drawn from the scientific and professional literature and policy documents on this subject. Results: The impact of crime on tourism can be seen on two levels: the macro and micro levels. The impact of crime on the macro level refers to its effects on society in general, on the social community or tourist destination, and the impact of crime at the micro level refers to the effects of crime on individuals. The most significant impact of crime on a tourist destination is the negative image of the destination, resulting in reduced tourist demand. The impact of crime on the micro level is evident in the influence on the behaviour and attitudes of tourists, and their decision to visit or revisit a destination where criminal incidents happen. Conclusions: Crime can have a very negative impact on tourism and security in tourism can not be taken for granted, so it is necessary to make significant efforts to ensure a safe environment for tourists. In order to prevent crime and to create a safe environment for tourists, it is necessary to ensure the cooperation all stakeholders involved in tourism: the tourism industry, local community, national authorities, police and state agencies.

The financial numbers game is unfortunately alive and doing well. One of the forensic accounting techniques is based on Benford’s Law and is used for the detection of unusual transactions, anomalies or trends. The aim of this paper is to test whether the financial statements of Croatian companies deviate from Benford’s Law distribution. The financial statements of 24 companies that are in the pre-bankruptcy settlement process and 24 companies that are not in the pre-bankruptcy settlement process were analysed using the Benford’s Law test of the first digit distribution for the period from 2015 to 2018. The data used to calculate the first digits of distribution were taken from the Zagreb Stock Exchange. The chi-square test has shown that the observed companies that are not in the process of pre-bankruptcy settlement do not have the first digit distribution which follows the Benford’s Law distribution. The Kolmogorov-Smirnov Z test has shown that the distribution of the first digits from the financial statements of companies listed on the Zagreb Stock Exchange fits to Benford’s Law distribution.