Daria Hontar

The purpose of the study consists in the investigation of the leasing market and determining the prospects of its development in Ukraine, which will make possible for lessors to justify the choice of their strategies. There were forecasted values of the analyzed indicators of leasing market for the following three periods: the third quarter of 2016, fourth quarter of 2016, first quarter of 2017. It was proposed to calculate the integral development index of leasing services in Ukraine based on the amount of leasing companies in Ukraine, the amount of financial leasing contracts, the share of long-term lease agreements, the value of financial leasing contracts, the proportion of borrowed funds in the structure of leasing transactions financing, the share reward the lessor for the leased property in the structure of the lease payments, in the amount of leasing companies in Ukraine, the amount of financial leasing contracts, the share of long-term lease agreements, the value of financial leasing contracts, the proportion of borrowed funds in the structure of leasing transactions financing, the share reward the lessor for the leased property in the structure of the lease payments. The authors defined the growth of Ukrainian leasing market in the first quarter of 2017. The proposed integral development index is applicable both on regional and international level. The results of study can be used for substantiation of the choice of lessors’ strategies by developing alternative strategic decisions, the optimal use of which should lead to a further growth of the leasing market.

Keywords: leasing, leasing companies, methods of multivariate statistical analysis, forecasting, market of leasing services.
JEL Classification: C53, G17, G21

The article proposes a tool for managing money laundering risk based on the definition of the level of coherence of financial companies and credit unions, the application of which will contribute to introduction of a risk-based approach to anti-money laundering, terrorist financing and proliferation of weapons of mass destruction. It was revealed that among the investigated during 2010-2017 financial corporations and credit unions there are financial conglomerates. This confirms the existence of close ties between them. Associated financial companies and credit unions may form or join networks that can be used for possible money laundering. It was established that the share of connected credit unions and financial companies corresponds to the principle of Pareto – 20:80. The proposed methodological support allowed selecting a large number of independent credit unions and financial companies. This will help to prevent the impact of the risk of connected individuals on the high ability of the borrower to fulfill their loan obligations and not to be involved in processes for money laundering using networks. Meanwhile, dedicated joint financial institutions belong to a high-risk group for controlling their financial operations to prevent the legalization of proceeds from crime.

The study aims at developing an approach to determining the bank connectivity level. This will contribute to implementing a risk-oriented approach to counteracting money laundering, terrorist financing and the proliferation of mass destruction weapons. The article proposes to assess the degree of bank connectivity and determine the impact of these circumstances on money laundering risk using banks from foreign banking groups, whose capital share in the Ukrainian banking system amounts to more than 40 percent. Using the resulting correlation dependencies, two-dimensional binary matrices were constructed, which became the basis for creating graphs of links between banks. The institutions under study are found to be predominantly connected in terms of their sets (varieties), since the average proportion of banks with close direct links is over half, and the non-connectivity coefficient for them is about 40%. Each surveyed bank, on average, has direct links with eight other banks and inverse links with four other banks. Considering banks as tops of the graph, one can assume that there is a hidden relationship between some banks. This approach allows calculating all existing relationships between banks to assess risk. Transforming the graph from non-oriented to oriented made it possible to identify and clearly demonstrate possible directions of links between the investigated financial institutions, which should be further verified to determine the risk of money laundering, terrorist financing, etc.