The article is dedicated to the issues of improving a system of organizational providing of investment constructional activity at the real estate market of Ukraine. The authors suggest modern approaches to organizing different stages of investment and construction process. In particular, legal bases for organizing real estate development project concept design stage are analyzed and the ways of permissible procedures simplifying in construction are defined. Suggestions concerning choice of approaches to evaluating real estate projects development effectiveness of realization are made, where an important place belongs to development land improvement estimation. Real estate development project estimation methodology for various real estate types considering special aspects of conducting marketing research is offered. The article conclusion contains means recommended for implementing by real estate development organizations while designing their strategy of development.

Objective. The aim is to enhance the efficiency of diagnostics for determining the level of air attack safety through the practical integration principles of artificial intelligence. Methodology. Models and technologies for safety diagnostics of the region (territorial community) have been explored. The process of building an artificial intelligence model requires differentiation of objects at a level to accumulate assessments-characteristics of aerial vehicles. The practical integration principles of artificial intelligence into the forecasting technology are based on the Region Safety Index, used for constructing machine learning models. The optimal machine learning model of the proposed approach is selected from a list of several models. Results. A technology for predicting the level of regional safety based on the Safety Index has been developed. The recommended optimal model is the Random Forest model ([('max_depth', 13), ('max_features', 'sqrt'), ('min_samples_leaf', 1), ('min_samples_split', 2), ('n_estimators', 79)]), demonstrating the most effective quality indicators of MAE; MAX; RMSE 0.005; 0.083; 0.0139, respectively. Scientific Novelty. The proposed approach is based on a linear model of the Region Safety Index, which, unlike existing ones, takes into account the interaction of factors. This allows for advantages of the proposed method over existing approaches in terms of the root mean square error of 0.496; 0.625, respectively. In turn, this influences the quality of machine learning models. Practical Significance. The proposed solutions are valuable for diagnosing the level of safety in the region of Ukraine, particularly in the context of air attacks.

The article updates the problem of the functioning and development of the insurance market of Ukraine, which needs drastic changes. This is a consequence of the development of the digital economy and the introduction of innovative technologies into all spheres of economic activity through the expansion of e-commerce, e-business, the use of various mobile applications and platforms that are widely Available and provide competitive advantages. It is emphasized that the processes of globalization of financial markets in the world economy have already significantly transformed the relations of insurance companies with agents in the market and prompted the modernization of business models and technological processes. Special attention in the study is given to the analysis of changes in the insurance market of Ukraine, which are taking place against the background of the Covid-19 pandemic and the full-scale military invasion of the Russian Federation. Based on the analysis of the state of Ukrainian insurers, it was concluded that the acquired level of digitalization of the financial space acted as a positive lever for preserving financial stability for Ukrainian insurance companies and allowed them to reshape the vast majority of business processes and communications with clients into a remote format in a short time.