The paper used methods for time series forecasting and risk analysis of the quality of the consumer loan portfolio and compare their quality, used technique of scoring and its implementation through the use of discriminant analysis and neural networks to predict the likelihood of timely repayment of the loan borrower. Forecasting is done in software product «Statistica». In this paper we implemented ARIMA model, seasonal decomposition, exponential smoothing, discriminant analysis and neural network techniques.

Currently, the development of road networks is growing rapidly. There is a need in the accession of new sections to the existing roads. The present work sets the task of finding Steiner points for three points. While carrying out this work, there was learnt the basics of graph theory, the methods of finding shortest networks and defined the Steiner problem. There was also implemented an application in Delphi 2010 determining the Steiner point, the minimum path (section) length, and calculating travel time and approximate cost of construction for the resulting road section.