Ivan Horvat, Mirjana Pejić Bach and Marjana Merkač Skok
Background: Fraud attempts create large losses for financing subjects in modern economies. At the same time, leasing agreements have become more and more popular as a means of financing objects such as machinery and vehicles, but are more vulnerable to fraud attempts. Objectives: The goal of the paper is to estimate the usability of the data mining approach in discovering fraud in leasing agreements. Methods/Approach: Real-world data from one Croatian leasing firm was used for creating tow models for fraud detection in leasing. The decision tree method was used for creating a classification model, and the CHAID algorithm was deployed. Results: The decision tree model has indicated that the object of the leasing agreement had the strongest impact on the probability of fraud. Conclusions: In order to enhance the probability of the developed model, it would be necessary to develop software that would enable automated, quick and transparent retrieval of data from the system, processing according to the rules and displaying the results in multiple categories.
Mirjana Pejić Bach, Marjana Merkač Skok and Dalia Suša
Although many researchers agree that environmental and personal characteristics are important for becoming an entrepreneur, it is still not clear if their influence is equally significant. Numerous authors have pointed out unresolved matters regarding the relationship among innovativeness, gender, and entrepreneurial intensions. The aim of this paper is to explore the impact of gender and country of origin in relation to entrepreneurial intentions and innovative cognitive style. Research was conducted using a sample of students majoring in information and communication technologies from Croatia and Slovenia. The results revealed the influence of gender, country, attitudes toward entrepreneurship, and innovative cognitive style on entrepreneurial intentions.