Using Telegram Bots for Personalized Financial Advice for Staff of Manufacturing Engineering Enterprises

This paper covers the research on using instant messengers’ chatbots to provide automated financial advice to manufacturing engineering enterprises employees in the scope of a chatbot application, which helps to calculate personal savings programs to ensure a constant level of consumption. The paper aims to develop telegram bots for personalized financial advice of manufacturing engineering enterprises staff. The application uses a model of life-cycle hypothesis and generates a customized saving plan based on the information provided by a user. The factors affecting decisions regarding advice include previous satisfaction with decision-making, investors’ preferences, perceived difficulty, the relationship between financial literacy, expertise, and confidence. Different approaches to developing messengers’ bots have been compared. The paper also gives a brief overview of the life-cycle approach, which suggests that finance managers plan consumption and savings behavior over the whole life cycle of their personnel. The research is focused on the Telegram platform and includes an overview of Telegram Bot API and the process of chatbot development using Java programming language.