USING JAVASCRIPT CAPABILITIES IN BUILDING SOFTWARE TOOLS FOR FINANCIAL ASSISTANTS
DOI:
https://doi.org/10.31891/Keywords:
financial recommendations, decision-making, large language models, machine learning, software models, financial instrumentsAbstract
This work is dedicated to the development and implementation of an intelligent system for the effective management of own financial assets. There are a lot of different financial assistants on the market, but it is hard to trust them because, as usual, there is no scientific background behind. A real financial decision-making process is complex and can involve different techniques in parallel to guarantee the best decision. In the meantime, the applicability of AI technology is increasingly growing, proposing new opportunities for investigation. The main goal of the project is the creation of a multifunctional tool that helps users manage both cryptocurrency and fiat assets more efficiently. The platform provides real-time recommendations based on automated analysis of market data and user wallet information. Additionally, the system supports integration with cryptocurrency wallets, the Monobank API, and other financial tools, enabling users to manage all their assets within a single interface. In the implementation, Binance API is used to obtain real-time market data, CoinGecko API to gather additional analytics and historical information, Infura for secure and convenient reading of data from cryptocurrency wallets, and Monobank API to monitor bank accounts and transactions.
A distinctive feature of the platform is the use of a trained machine learning model that predicts the growth or decline of a selected cryptocurrency based on historical and current market data. This enables the generation of personalised investment recommendations and timely alerts about potential market changes.
The developed solution stands out for its ability to combine traditional bank accounts and cryptocurrency assets into a single platform with a simple and intuitive interface. In addition to optimising financial management processes, the system aims to improve users’ financial literacy by providing analytical data and advice that help reduce investment risks and increase portfolio profitability.
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