ONLINE AGNOSTIC RECOMMENDATION SYSTEM FOR APPLICATION IN INVESTMENT FUNDS - Antonio Newton Licciardi Jr (DMPHub, 2022)
Considering the reduction on basic interest rate in Brazil, the bonus payments obtained through “caderneta de poupança” (a popular and traditional brazilian special type of account which total value is correct by inflantion index and standard low taxes, basically), which is the most used investment in the country, hade been becoming deficitary. This fact has led to a growth in the number of individuals investing in the stock market  looking for more attractive profitability. The system objective is make available an agnostic system that analyzes in real time the investment funds that have shown the best performance and can suggest, for people with low level of financial knowledge, the funds portfolio that best suits the investor profile. In order to build the system, open fund databases made available by CVM in Brazil (dados.gov.br) and the investor's potential profile are explored, using the most appropriate user friendly computational tool. Besides, a system cliente survey deployed have its answers compiled and analysed in a paper tied to system implementation.