Forecasting the income of a management company based on machine learning technologies

Abstract

Significantly frolicking under the management of large developers, the housing and utilities sector, just like some other business, requires clear financial and resource planning. A qualitative forecast that takes into account relevant data not only retrospective data on sales volumes of services, but also the size of utility payments, prices for housing and communal services, etc., allows effective planning of business management activities. This paper is devoted to the problem of forecasting cash receipts for a management company. Based on the analysis of publications devoted to the issues of forecasting and planning income for management companies, it is revealed that the list is limited, indicating the narrow focus of the problem and its certain complexity. The study proposes a variant algorithm for forecasting the income of a management company engaged in integrated services in the domain of housing and communal services and providing living conditions for residents of apartment buildings, which is based on the method of machine learning.

Keywords

• housing and communal services
• management company
• forecasting
• machine learning
• gradient boosting